Method and system for modifying image quality

ABSTRACT

A method and system with which quality of an image derived from or addressed to a chain of appliances can be modified. Formatted information related to defects of the appliances is employed. The method and system: compile directories of sources of formatted information related to the appliances, search automatically for the formatted information related to the appliances, and modify the image automatically by image-processing software and/or image-processing components by taking into account the obtained formatted information. The formatted information can be modified as a function of variable characteristics of the image to be processed and/or the appliances. With the method and system it is possible to process images derived from appliances that have diverse origins and that have been commercialized gradually over time. Such a method and system are applicable to processing of photographic or video images and in optical instrumentation, industrial controls, robotics, metrology, etc.

BACKGROUND OF THE INVENTION Field of Invention

The present invention relates to a method and a system for modifying thequality of at least one image derived from or addressed to an appliancechain.

SUMMARY OF THE INVENTION

The invention relates to a method for modifying the quality of at leastone image derived from or addressed to a specified appliance chain. Thespecified appliance chain includes at least one image-capture applianceand/or at least one image-restitution appliance. The image-captureappliances and/or the image-restitution appliances that have beencommercialized gradually by distinct economic players belong to anindeterminate set of appliances. The appliances of the set of appliancesexhibit defects that can be characterized by formatted information. Forthe image in question, the method includes the following stages:

-   -   the stage of compiling directories of the sources of formatted        information related to the appliances of the set of appliances,    -   the stage of searching automatically, among the formatted        information compiled in this way, for specific formatted        information related to the specified appliance chain,    -   the stage of modifying the image automatically by means of        image-processing software and/or image-processing components,        taking into account the specific formatted information obtained        in this way.

Preferably, according to the invention, the method is such that theautomatic search is performed by means of indices obtained directly orindirectly from an analysis of:

-   -   the image, and/or    -   the appliances of the appliance chain, and/or    -   the means for loading the image into the image-processing        software or components, and/or    -   the means for loading the image modified by the image-processing        software or components to the restitution means.

Preferably, according to the invention, the appliances of the appliancechain are identified by identifiers, especially a bar code. The analysisfor the purpose of searching for the specific formatted informationincludes the stage of determining the identifiers.

Preferably, according to the invention, the method is such that theimage, the index and/or the identifier are contained in the same file.It results from the combination of technical features that it ispossible to employ the method according to the invention a posteriori inthe case in which certain appliances of the chain were commercializedbefore the formatted information relating to them was established.

Preferably, according to the invention, the method is such that theimage and at least one part of the specific formatted information arecontained in the same image file. It results from the combination oftechnical features that it is possible to search automatically for theformatted information in the image file.

Preferably, according to the invention, the method additionally includesthe stage of storing at least part of the formatted information inadvance in a database. The method additionally includes the stage ofupdating the database.

Preferably, according to the invention, the method is such that one ofthe appliances of the appliance chain is provided with at least onevariable characteristic depending on the image, especially the focallength. A fraction of the specific formatted information is related tothe defects of the appliance provided with the variable characteristic.The method additionally includes the following stages:

-   -   the stage of determining the value of the variable        characteristics for the said image;    -   the stage of determining the fraction of the said specific        formatted information by taking into account the variable        characteristic values obtained in this way.

Employment of the method for an appliance provided with a variablecharacteristic therefore amounts to employment of the method for anappliance that does not have any variable characteristic.

Preferably, according to the invention, the image is contained in afile. The method is such that, to determine the value of the variablecharacteristic, there are used data present in the file, especially datasuch as focal length, in a format such as the Exif standard. It resultsfrom the combination of technical features that it is possible to employthe method according to the invention a posteriori in the case in whichthe appliance provided with the variable characteristic wascommercialized before the formatted information relating to it wasestablished.

Preferably, according to the invention, the method is such that, tomodify the quality of at least one image derived from or addressed to anappliance chain:

-   -   there is determined a virtual appliance exhibiting defects        equivalent to at least part of the defects, referred to        hereinafter as original defects, of at least one appliance of        the appliance chain,    -   there is determined the virtual formatted information related to        the defects of the virtual appliance,    -   to determine the specific formatted information related to the        set of appliances of the appliance chain, the virtual formatted        information is substituted for the specific formatted        information related to the original defects.

It results from the combination of technical features that, in this way,there is obtained formatted information which is simpler to employ andwith which the modifications to be made to the image can be calculatedmore rapidly and/or by using less memory and/or with greater precision.

Preferably, according to the invention, the method is designed to modifythe quality of at least one color plane of a color image. The colorplane is characterized by a specified color. The specific formattedinformation additionally includes data related to the specified color.To modify the image, a color plane is calculated using the data relatedto the specified color and to the image.

Preferably, according to the invention, the method additionallyincludes, in the case in which the process of searching for specificformatted information is unsuccessful for one of the appliances of theappliance chain, the stage of calculating the unknown formattedinformation.

Preferably, according to the invention, the method additionally includesthe stage of calculating the unknown formatted information related to anappliance of the appliance chain:

-   -   by measuring the defects of the appliance, and/or    -   by simulating the appliance.

Preferably, according to the invention, the method additionallyincludes, for an image-capture appliance of the appliance chain, thestage of calculating the unknown formatted information:

-   -   by constructing a synthetic-image class by specified        mathematical projections of at least one reference scene onto a        surface,    -   by capturing at least one reference image of each reference        scene by means of the image-capture appliance,    -   by choosing, within a set of parameterizable transformation        models, that with which the reference image can be transformed        to a transformed image close to the synthetic-image class of the        reference scene.

The transformed image exhibits a deviation compared with thesynthetic-image class. The unknown formatted information is composed atleast partly of parameters of the chosen parameterizable transformationmodels.

Preferably, according to the invention, the method additionallyincludes:

-   -   the stage of calculating the deviations between the transformed        image and the synthetic-image class,    -   the stage of associating the deviations with the said unknown        formatted information.

It results from the combination of technical features that it ispossible to deduce standardized information about the scenes in threedimensions. It results from the combination of technical features thatit is possible to combine a plurality of images obtained from aplurality of image-capture appliances having undergone the sameformatting process.

Preferably, according to the invention, the method is such that one ofthe appliances of the appliance chain is provided with at least onevariable characteristic depending on the image, especially the focallength and/or the aperture. A fraction of the specific formattedinformation is related to the defects off the appliance provided withthe variable characteristic or characteristics. Each variablecharacteristic is capable of being associated with a value to form acombination composed of the set of variable characteristics and values.The method additionally includes the stage of determining the fractionof unknown formatted information:

-   -   by selecting predetermined combinations,    -   by employing a process of iteration of the preceding stages of        the method for each of the predetermined combinations,    -   by employing a process of interpolation of the unknown formatted        information related to an arbitrary combination, from the        unknown formatted information obtained at the end of the        iteration process.

Preferably, according to the invention, the method additionallyincludes, for an image-restitution means of the appliance chain, thestage of producing data characterizing the defects of theimage-restitution means, especially the distortion characteristics. Theunknown formatted information is composed at least partly of datacharacterizing the defects of the restitution means.

Preferably, according to the invention, the method is such that thespecific formatted information related to one appliance or to aplurality of appliances of the appliance chain is determined in such away that it can be applied to similar appliances. It results from thecombination of technical features that only a limited quantity offormatted information is needed for the method to be employed.

Preferably, according to the invention, the method is such that theimage includes associated information, especially a digital signal. Thestages of the method are employed in such a way that they conserve ormodify the associated information.

Preferably, according to the invention, the method additionally includesthe stage of associating information with the modified image, especiallyinformation indicating that it has been modified.

Preferably, according to the invention, the method is more particularlydesigned to modify the visual quality of the image for an observer. Theformatted information related to the defects of the appliances of theappliance chain additionally includes the formatted information relatedto the vision characteristics of the observer, especially functionalanomalies of the eyes and/or of the brain of the observer.

Application

The invention also relates to an application of the method describedhereinabove. The object of the application is to improve the quality ofimages processed by the image-processing software or theimage-processing components, by correcting for the effects of at leastone of the defects of the appliances of the appliance chain. It resultsfrom the combination of technical features that the quality of theprocessed images is improved if not perfect, without having to rely onexpensive appliances.

Preferably, the object of the application is that the quality of imagesprocessed by the image-processing software or the image-processingcomponents be comparable with that of images produced with a referenceappliance chain.

Preferably, the application is such that, for the quality of theprocessed images to be comparable with that of images produced with areference appliance chain, formatted information related to theappliance chain is produced by taking into account the defects of thereference appliance chain.

System

The invention relates to a system for modifying the quality of at leastone image derived from or addressed to a specified appliance chain. Thespecified appliance chain includes at least one image-capture applianceand/or at least one image-restitution appliance. The image-captureappliances and/or the image-restitution appliances that have beencommercialized gradually by distinct economic players belong to anindeterminate set of appliances. The appliances of the set of appliancesexhibit defects that can be characterized by formatted information. Forthe image in question, the system includes data-processing means capableof:

-   -   compiling directories of the sources of formatted information        related to the appliances of the set of appliances,    -   searching automatically, among the formatted information        compiled in this way, for specific formatted information related        to the specified appliance chain,    -   modifying the image automatically by means of image-processing        software and/or image-processing components, taking into account        the specific formatted information obtained in this way.

Preferably, according to the invention, the system is such that thedata-processing means perform the search automatically by means of anindex. The index is obtained directly or indirectly by analysis meansfrom an analysis of:

-   -   the image, and/or    -   the appliances of the appliance chain, and/or    -   the means for loading the image into the image-processing        software or components, and/or    -   the means for loading the image modified by the image-processing        software or components to the restitution means.

Preferably, according to the invention, the appliances of the appliancechain are identified by identifiers, especially a bar code. The analysismeans include means for determining the identifiers.

Preferably, according to the invention, the system is such that theimage, the index and/or the identifier are contained in the same file.

Preferably, according to the invention, the system is such that theimage and at least one part of the specific formatted information arecontained in the same image file.

Preferably, according to the invention, the system additionally includesstorage means for storing at least part of the formatted information inadvance in a database. The system additionally includes updating meansfor updating the database.

Preferably, according to the invention, the system is such that one ofthe appliances of the appliance chain is provided with at least onevariable characteristic depending on the image, especially the focallength. A fraction of the specific formatted information is related tothe defects of the appliance provided with the variable characteristic.The system additionally includes calculating means for determining:

-   -   the value of the variable characteristics for the image in        question;    -   the fraction of the said specific formatted information by        taking into account the variable values obtained in this way.

Preferably, according to the invention, the image is contained in afile. The system is such that, to determine the value of the variablecharacteristic, the system includes data-processing means for processingthe data present in the file, especially data such as focal length, in aformat such as the Exif standard.

Preferably, according to the invention, the system is such that, tomodify the quality of at least one image derived from or addressed to anappliance chain, the system includes data-processing means fordetermining:

-   -   a virtual appliance exhibiting defects equivalent to at least        part of the defects, referred to hereinafter as original        defects, of at least one appliance of the appliance chain,    -   the virtual formatted information related to the defects of the        virtual appliance.

The system is such that, to determine the specific formatted informationrelated to the set of appliances of the appliance chain, thedata-processing means include substitution means for substituting thevirtual formatted information for the specific formatted informationrelated to the original defects.

Preferably, according to the invention, the system is designed to modifythe quality of at least one color plane of a color image. The colorplane is characterized by a specific color. The specific formattedinformation additionally includes data related to the specified color.The system includes calculating means for calculating a color planeusing the data related to the specified color and to the image.

Preferably, according to the invention, the system additionallyincludes, in the case in which the process of searching for specificformatted information is unsuccessful for one of the appliances of theappliance chain, calculating means for calculating the unknown formattedinformation.

Preferably, according to the invention, the system is such that thecalculating means for calculating the unknown formatted informationrelated to an appliance of the appliance chain include processing meansfor measuring the defects of the appliance and/or for simulating theappliance.

Preferably, according to the invention, the method additionallyincludes, for an image-capture appliance of the appliance chain,calculating means for calculating the unknown formatted information byconstructing a synthetic-image class by specified mathematicalprojections of at least one reference scene onto a surface. Theimage-capture appliance captures at least one reference image of eachreference scene. The calculating means calculate the unknown formattedinformation by choosing, within a set of parameterizable transformationmodels, that with which the reference image can be transformed to atransformed image close to the synthetic-image class of the referencescene. The transformed image exhibits a deviation compared with thesynthetic-image class. The unknown formatted information is composed atleast partly of parameters of the chosen parameterizable transformationmodels.

Preferably, according to the invention, the system additionally includesdata-processing means for:

-   -   calculating the deviations between the transformed image and the        synthetic-image class,    -   associating the deviations with the unknown formatted        information.

Preferably, according to the invention, the system is such that one ofthe appliances of the appliance chain is provided with at least onevariable characteristic depending on the image, especially the focallength and/or the aperture. A fraction of the specific formattedinformation is related to the defects of the appliance provided with thevariable characteristic or characteristics. Each variable characteristicis capable of being associated with a value to form a combinationcomposed of the set of variable characteristics and values. The systemadditionally includes data-processing means for determining the fractionof unknown formatted information:

-   -   by selecting predetermined combinations,    -   by employing, for each of the predetermined combinations, a        process of iteration of the calculating means and of the        data-processing means described hereinabove,    -   by employing a process of interpolation of the unknown formatted        information related to an arbitrary combination, from the        unknown formatted information obtained at the end of the        iteration process.

Preferably, according to the invention, the system additionallyincludes, for an image-restitution means of the appliance chain,data-processing means for producing data characterizing the defects ofthe image-restitution means, especially the distortion characteristics.The unknown formatted information is composed at least partly of datacharacterizing the defects of the restitution means.

Preferably, according to the invention, the system is such that thespecific formatted information related to one appliance or to aplurality of appliances of the appliance chain is determined in such away that it can be applied to similar appliances.

Preferably, according to the invention, the system is such that theimage includes associated information, especially a digital signal. Thesystem is employed in such a way that it conserves or modifies theassociated information.

Preferably, according to the invention, the system additionally includesdata-processing means for associating information with the modifiedimage, especially information indicating that it has been modified.

Preferably, according to an alternative embodiment of the invention, thesystem is more particularly designed to modify the visual quality of theimage for an observer. The formatted information related to the defectsof the appliances of the said appliance chain additionally includes theformatted information related to the vision characteristics of the saidobserver, especially functional anomalies of the eyes and/or of thebrain of the said observer.

BRIEF DESCRIPTION OF THE DRAWINGS

Other characteristics and advantages of the invention will becomeapparent upon reading of the description of practical examples of theinvention, provided on a non-limitative basis, and of the figures,wherein:

FIG. 1 illustrates a schematic view of image capture,

FIG. 2 illustrates a schematic view of image restitution,

FIG. 3 illustrates a schematic view of the pixels of an image,

FIGS. 4 a and 4 b illustrate two schematic views of a reference scene,

FIG. 5 illustrates the organizational diagram of the method with whichthe difference between the mathematical image and the corrected imagecan be calculated,

FIG. 6 illustrates the organizational diagram of the method with whichthe best restitution transformation for an image-restitution means canbe obtained,

FIG. 7 illustrates a schematic view of the elements composing the systemto which the invention is applied,

FIG. 8 illustrates a schematic view of fields of formatted information,

FIG. 9 a illustrates a schematic front view of a mathematical point,

FIG. 9 b illustrates a schematic front view of a real point of an image,

FIG. 9 c illustrates a schematic side view of a mathematical point,

FIG. 9 d illustrates a schematic profile view of a real point of animage,

FIG. 10 illustrates a schematic view of an array of characteristicpoints,

FIG. 11 illustrates the organizational diagram of the method with whichthe formatted information can be obtained,

FIG. 12 illustrates the organizational diagram of the method with whichthe best transformation for an image-capture appliance can be obtained,

FIGS. 13 a to 13 c illustrate connection diagrams of practical examplesof systems with which an image can be corrected,

FIGS. 14 a to 14 c illustrate organizational diagrams of practicalexamples of methods with which automatic image correction can beemployed,

FIG. 15 illustrates an organizational diagram of a method with which avirtual appliance can be substituted for an appliance chain,

FIG. 16.1 illustrates a diagram of an appliance possessing defects,

FIG. 16.2 illustrates a diagram of an appliance possessing variablecharacteristics,

FIG. 16.3 illustrates a diagram that includes a vision defect or defectsof an observer,

FIG. 16.4 illustrates a diagram of processing of the characteristics ofa virtual appliance,

FIG. 16.5 illustrates a diagram of the addition of informationassociated with a corrected image,

FIG. 16.6 illustrates a diagram indicating how the formatted informationmay relate to one or more lots of appliances,

FIG. 17 illustrates a description of an example of employment of themethod and system according to the invention,

FIG. 18 illustrates a description of an example of employment of themethod and system according to the invention in the case of a colorimage.

DETAILED DESCRIPTION OF THE INVENTION

Referring in particular to FIG. 17, a description will be given of theconcept of appliance chain P3. The appliances of appliance chain P3,especially image-capture appliances and/or image-restitution appliances,are being progressively commercialized by distinct economic players, andthey belong to an indeterminate set of appliances also defined as setP75 of appliances.

Within the meaning of the invention, an appliance can be in particular:

-   -   an image-capture appliance, such as a disposable photo        appliance, a digital photo appliance, a reflex appliance, a        scanner, a fax machine, an endoscope, a camcorder, a        surveillance camera, a game, a camera integrated into or        connected to a telephone, to a personal digital assistant or to        a computer, a thermal camera or an echographic appliance,    -   an image-restitution appliance or image-restitution means 19,        such as a screen, a projector, a television set, virtual-reality        goggles or a printer,    -   an appliance, including its installation, such as a projector, a        screen and the manner in which they are positioned,    -   the positioning of an observer relative to an image-restitution        appliance, which introduces parallax errors in particular,    -   a human being having vision defects, such as astigmatism,    -   an appliance which it is hoped can be emulated, to produce        images having, for example, an appearance similar to those        produced by an appliance of the Leica brand,    -   an image-processing device, such as zoom software, which has the        edge effect of adding blurring,    -   a virtual appliance equivalent to a plurality of appliances,

A more complex appliance, such as a scanner/fax/printer, aphoto-printing Minilab, or a videoconferencing appliance can be regardedas an appliance or as a plurality of appliances.

An appliance chain P3 is defined as a set of appliances. The concept ofappliance chain P3 may also include a concept of order.

The following examples constitute appliance chains P3:

-   -   a single appliance,    -   an image-capture appliance and an image-restitution appliance,    -   a photo appliance, a scanner or a printer, for example in a        photo-printing Minilab,    -   a digital photo appliance or a printer, for example in a        photo-printing Minilab,    -   a scanner, a screen or a printer, for example in a computer,    -   a screen or projector, and the eye of a human being,    -   one appliance and another appliance which it is hoped can be        emulated,    -   a photo appliance and a scanner,    -   an image-capture appliance and image-processing software,    -   image-processing software and an image-restitution appliance,    -   a combination of the preceding examples,    -   another set of appliances.

Defect

Referring in particular to FIG. 17, a description will now be given ofthe concept of defect P5. A defect P5 of an appliance of the applianceset P75 is defined as a defect related to the characteristics of theoptical system and/or of the sensor and/or of the electronic unit and/orof the software integrated in an appliance; examples of defects P5include distortion, blurring, vignetting, chromatic aberrations,rendering of colors, flash uniformity, sensor noise, grain, astigmatism,spherical aberration.

Image

Referring in particular to FIG. 17, a description will now be given ofthe concept of image P2. Image P2 is defined as a digital image capturedor modified or restituted by an appliance. Image P2 may originate froman appliance of appliance chain P3. Image P2 may be addressed to anappliance of appliance chain P3. More generally, image P2 may be derivedfrom and/or addressed to appliance chain P3. In the case of animatedimages, such as video images, composed of a time sequence of fixedimages, image P2 is defined as one fixed image of the sequence ofimages.

Formatted Information

Referring in particular to FIG. 17, a description will now be given ofthe concept of formatted information 15. Formatted information 15 isdefined as data related to the defects P5 of one or more appliances ofappliance chain P3 and enabling image-processing means to modify thequality of images P2 by making allowance for the defects P5 ofappliance. To produce the formatted information 15, there can be usedvarious methods and systems based on measurements and/or captures orrestitution of references, and/or simulations.

To produce the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for producing formattedinformation related to the defects of appliances of an appliance chainand formatted information addressed to image-processing means.” Thatapplication describes a method for producing formatted information 15related to the defects P5 of appliances of an appliance chain P3. Theformatted information 15 is addressed to image-processing means, inparticular software, with a view to modifying the quality of the imagesprocessed by the image-processing means. Appliance chain P3 is composedin particular of at least one image-capture appliance and/or at leastone restitution means and/or at least one observer. The method comprisesthe stage of producing data characterizing the defects P5 of theappliances of appliance chain P3. The data are the formatted information15.

To produce the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for producing formattedinformation related to geometric distortions”. That applicationdescribes a method for producing formatted information 15 related to theappliances of an appliance chain P3. Appliance chain P3 is composed inparticular of at least one image-capture appliance and/or at least oneimage-restitution appliance. The method includes the stage of producingformatted information 15 related to the geometric distortions of atleast one appliance of the chain.

Appliance preferably makes it possible to capture or restitute an imageon a medium. Appliance contains at least one fixed characteristic and/orone variable characteristic depending on the image. The fixedcharacteristic and/or variable characteristic can be associated with oneor more values of characteristics, especially the focal length and/orthe focusing and their values of associated characteristics. The methodincludes the stage of producing, from a measured field, measuredformatted information related to the geometric distortions of theappliance. The formatted information 15 may include the measuredformatted information.

To produce the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for producing formattedinformation related to the defects of at least one appliance of a chain,especially to blurring”. That application describes a method forproducing formatted information 15 related to the appliances of anappliance chain P3. Appliance chain P3 is composed in particular of atleast one image-capture appliance and/or at least one image-restitutionappliance. The method includes the stage of producing formattedinformation 15 related to the defects P5 of at least one appliance ofthe chain. Preferably, appliance with which an image can be captured orrestituted contains at least one fixed characteristic and/or onevariable characteristic depending on the image (I). The fixed and/orvariable characteristics can be associated with one or more values ofcharacteristics, especially the focal length and/or the focusing andtheir values of associated characteristics. The method includes thestage of producing measured formatted information related to the defectsP5 of appliance from a measured field. The formatted information 15 mayinclude the measured formatted information.

To provide the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for providing formattedinformation in a standard format to image-processing means.” Thatapplication describes a method for providing formatted information 15 ina standard format to image-processing means, in particular softwareand/or components. The formatted information 15 is related to thedefects P5 of an appliance chain P3. The appliance chain P3 is composedin particular of at least one image-capture appliance and/or oneimage-restitution appliance. The image-processing means use theformatted information 15 to modify the quality of at least one image P2derived from or addressed to the appliance chain P3. The formattedinformation 15 comprises data characterizing the defects P5 of theimage-capture appliance, in particular the distortion characteristics,and/or data characterizing the defects of the image-restitutionappliance, in particular the distortion characteristics.

The method includes the stage of filling in at least one field of thestandard format with the formatted information 15. The field isdesignated by its field name, the field containing at least one fieldvalue.

To produce the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for reducing updatefrequency of image processing means”. That application describes amethod for reducing the update frequency of image-processing means, inparticular software and/or a component. The image-processing means makeit possible to modify the quality of the digital images derived from oraddressed to an appliance chain P3. Appliance chain P3 is composed inparticular of at least one image-capture appliance and/or at least oneimage-restitution appliance. Image-processing means employ formattedinformation 15 related to the defects P5 of at least one appliance ofappliance chain P3. The formatted information P3 depends on at least onevariable. The formatted information makes it possible to establish acorrespondence between one part of the variables and of the identifiers.By means of the identifiers it is possible to determine the value of thevariable corresponding to the identifier by taking the identifier andthe image into account. It results from the combination of technicalfeatures that it is possible to determine the value of a variable,especially in the case in which the physical significance and/or thecontent of the variable are known only after distribution ofimage-processing means. It also results from the combination oftechnical features that the time between two updates of the correctionsoftware can be spaced apart. It also results from the combination oftechnical features that the various economic players that produceappliances and/or image-processing means can update their productsindependently of other economic players, even if the latter radicallychange the characteristics of their product or are unable to force theirclient to update their products. It also results from the combination oftechnical features that a new functionality can be deployedprogressively by starting with a limited number of economic players andpioneer users.

To exploit the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for calculating atransformed image from a digital image and formatted information relatedto a geometric transformation”. That application describes a method forcalculating a transformed image from a digital image and formattedinformation 15 related to a geometric transformation, especiallyformatted information 15 related to the distortions and/or chromaticaberrations of an appliance chain P3. The method includes the stage ofcalculating the transformed image from an approximation of the geometrictransformation. It results therefrom that the calculation is economicalin terms of memory resources, in memory bandpass, in calculating powerand therefore in electricity consumption. It also results therefrom thatthe transformed image does not exhibit any visible or annoying defect asregards its subsequent use.

To exploit the formatted information 15, it is possible, for example, touse the method and the system described in the International PatentApplication filed on the same day as the present application in the nameof Vision IQ and entitled “Method and system for modifying a digitalimage, taking into account its noise”. That application describes amethod for calculating a transformed image from a digital image andformatted information 15 related to the defects P5 of an appliance chainP3. Appliance chain P3 includes image-capture appliances and/orimage-restitution appliances. Appliance chain P3 contains at least oneappliance. The method includes the stage of automatically determiningthe characteristic data from the formatted information 15 and/or thedigital image. It results from the combination of technical featuresthat the transformed image does not exhibit any visible or annoyingdefect, especially defects related to noise, as regards its subsequentuse.

Image-Processing Means

The following example illustrates one manner of producing the formattedinformation.

FIG. 1 illustrates a scene 3 containing an object 107, a sensor 101 andsensor surface 110, an optical center 111, an observation point 105 on asensor surface 110, an observation direction 106 passing throughobservation point 105, optical center 111, scene 3, and a surface 10geometrically associated with sensor surface 110.

FIG. 2 illustrates an image 103, an image-restitution means 19 and arestituted image 191 obtained on the restitution medium 190.

FIG. 3 illustrates a scene 3, an image-capture appliance 1 and an image103 composed of pixels 104.

FIGS. 4 a and 4 b illustrate two alternative versions of a referencescene 9.

FIG. 5 illustrates an organizational diagram employing a scene 3, amathematical projection 8 giving a mathematical image 70 of scene 3, areal projection 72 giving an image 103 of scene 3 for thecharacteristics 74 used, a parameterizable transformation model 12giving a corrected image 71 of image 103, the corrected image 71exhibiting a difference 73 compared with mathematical image 70.

FIG. 6 illustrates an organizational diagram employing an image 103, areal restitution projection 90 giving a restituted image 191 of image103 for the restitution characteristics 95 used, a parameterizablerestitution transformation model 97 giving a corrected restitution image94 of image 103, a mathematical restitution projection 96 giving amathematical restitution image 92 of corrected restitution image 94 andexhibiting a restitution difference 93 compared with restituted image191.

FIG. 7 illustrates a system comprising an image-capture appliance 1composed of an optical system 100, of a sensor 101 and of an electronicunit 102. FIG. 7 also illustrates a memory zone 16 containing an image103, a database 22 containing formatted information 15, and means 18 fortransmission of completed image 120 composed of image 103 and formattedinformation 15 to calculating means 17 containing image-processingsoftware 4.

FIG. 8 illustrates formatted information 15 composed of fields 90.

FIGS. 9 a to 9 d illustrate a mathematical image 70, an image 103, themathematical position 40 of a point, and the mathematical shape 41 of apoint, compared with the real position 50 and the real shape 51 of thecorresponding point of the image.

FIG. 10 illustrates an array 80 of characteristic points.

FIG. 11 illustrates an organizational diagram employing an image 103,the characteristics 74 used, and a database 22 of characteristics. Theformatted information 15 is obtained from the characteristics 74 usedand stored in database 22. The completed image 120 is obtained fromimage 103 and formatted information 15.

FIG. 12 illustrates an organizational diagram employing a referencescene 9, a mathematical projection 8 giving a synthetic image class 7 ofreference scene 9, and a real projection 72 giving a reference image 11of reference scene 9 for the characteristics 74 used. Thisorganizational diagram also employs a parameterizable transformationmodel 12 giving a transformed image 13 of reference image 11.Transformed image 13 exhibits a deviation 14 compared with syntheticimage class 7.

DEFINITIONS AND DETAILED DESCRIPTION

Other characteristics and advantages of the invention will becomeapparent on reading:

-   -   of the definitions explained hereinafter of the employed        technical terms, referring to the indicative and non-limitative        examples of FIGS. 1 to 12,    -   of the description of FIGS. 1 to 12.

Scene

Scene 3 is defined as a place in three-dimensional space, containingobjects 107 illuminated by light sources.

Image-Capture Appliance, Image, Image Capture

Referring to FIGS. 3 and 7, a description will now be given of what isunderstood by image-capture appliance 1 and image 103. Image-captureappliance 1 is defined as an appliance composed of an optical system100, of one or more sensors 101, of an electronic unit 102 and of amemory zone 16. By means of the said image-capture appliance 1, it ispossible to obtain, from a scene 3, fixed or animated digital images 103recorded in memory zone 16 or transmitted to an external device.Animated images are composed of a succession of fixed images 103 intime. The said image-capture appliance 1 can have the form in particularof a photographic appliance, of a video camera, of a camera connected toor integrated in a PC, of a camera connected to or integrated in apersonal digital assistant, of a camera connected to or integrated in atelephone, of a videoconferencing appliance or of a measuring camera orappliance sensitive to wavelengths other than those of visible light,such as a thermal camera.

Image capture is defined as the method by which image 103 is calculatedby image-capture appliance 1.

In the case in which an appliance is equipped with a plurality ofinterchangeable subassemblies, especially an optical system 100,image-capture appliance 1 is defined as a special configuration of theappliance.

Image-Restitution Means, Restituted Image, Image Restitution

Referring to FIG. 2, a description will now be given of what isunderstood by image-restitution means 19. Such an image-restitutionmeans 19 can have the form in particular of a visual display screen, ofa television screen, of a flat screen, of a projector, of virtualreality goggles, of a printer.

Such an image-restitution means 19 is composed of:

-   -   an electronic unit,    -   one or more sources of light, of electrons or of ink,    -   one or more modulators: devices for modulation of light, of        electrons or of ink,    -   a focusing device, having in particular the form of an optical        system in the case of a light projector or the form of        electron-beam focusing coils in the case of a CRT screen, or the        form of filters in the case of a flat screen,    -   a restitution medium 190 having in particular the form of a        screen in the case of a CRT screen, of a flat screen or of a        projector, the form of a print medium on which printing is        performed in the case of a printer, or the form of a virtual        surface in space in the case of a virtual-image projector.

By means of the said image-restitution means 19, it is possible toobtain, from an image 103, a restituted image 191 on restitution medium190.

Animated images are composed of a succession of fixed images in time.

Image restitution is defined as the method by which the image isdisplayed or printed by means of image restitution means 19.

In the case in which a restitution means 19 is equipped with a pluralityof interchangeable subassemblies or of subassemblies that can be shiftedrelative to one another, especially restitution medium 190,image-restitution means 19 is defined as a special configuration.

Sensor Surface, Optical Center, Focal Distance

Referring to FIG. 1, a description will now be given of what is definedas sensor surface 110.

Sensor surface 110 is defined as the shape in space drawn by thesensitive surface of sensor 101 of image-capture appliance 1 at themoment of image capture. This surface is generally plane.

An optical center 111 is defined as a point in space associated withimage 103 at the moment of image capture. A focal distance is defined asthe distance between this point 111 and plane 110, in the case in whichsensor surface 110 is plane.

Pixel, Pixel Value, Exposure Time

Referring to FIG. 3, a description will now be given of what isunderstood by pixel 104 and pixel value.

A pixel 104 is defined as an elemental zone of sensor surface 110obtained by creating a grid, generally regular, of the said sensorsurface 110. Pixel value is defined as a number associated with thispixel 104.

Image capture is defined as determining the value of each pixel 104. Theset of these values constitutes image 103.

During image capture, the pixel value is obtained by integration, overthe surface of pixel 104, during a time period defined as exposure time,of part of the light flux derived from scene 3 via optical system 100,and by converting the result of this integration to a digital value. Theintegration of the light flux and/or the conversion of the result ofthis integration to a digital value are performed by means of electronicunit 102.

This definition of the concept of pixel value is applicable to the caseof black-and-white or color images 103, whether they be fixed oranimated.

Depending on the cases, however, the part in question of the light fluxis obtained in various ways:

a) In the case of a color image 103, sensor surface 110 is generallycomposed of a plurality of types of pixels 104, associated respectivelywith light fluxes of different wavelengths, examples being red, greenand blue pixels.

b) In the case of a color image 103, there may also be a plurality ofsensors 101 disposed side-by-side, each receiving part of the lightflux.

c) In the case of a color image 103, the colors used may be differentfrom red, green and blue, such as for North American NTSC television,and they may exceed three in number.

d) Finally, in the case of an interlaced television scanning camera, theanimated images produced are composed of an alternation of images 103containing even-numbered lines and of images 103 containing odd-numberedlines.

Configuration Used, Adjustments Used, Characteristics Used

The configuration used is defined as the list of removable subassembliesof image-capture appliance 1, such as optical system 100 which, if it isinterchangeable, is mounted on image-capture appliance 1. Theconfiguration used is characterized in particular by:

-   -   the type of optical system 100,    -   the serial number of optical system 100 or any other        designation.

Adjustments used are defined as:

-   -   the configuration used as defined hereinabove, as well as    -   the value of the manual or automatic adjustments available in        the configuration used and having an impact on the content of        image 103. These adjustments may be made by the user, especially        by means of pushbuttons, or may be calculated by image-capture        appliance 1. These adjustments may be stored in the appliance,        especially on a removable medium, or on any device connected to        the appliance. These adjustments may include in particular the        adjustments of focusing, diaphragm and focal length of optical        system 100, the adjustments of exposure time, the adjustments of        white balance, and the integrated image-processing adjustments,        such as digital zoom, compression and contrast.

Characteristics 74 used or set of characteristics 74 used are definedas:

a) Parameters related to the intrinsic technical characteristics ofimage-capture appliance 1, determined during the phase of design ofimage-capture appliance 1. For example, these parameters may include theformula of optical system 100 of the configuration used, which impactsthe geometric defects and the sharpness of the captured images; theformula of optical system 100 of the configuration used includes inparticular the shape, the arrangement and the material of the lenses ofoptical system 100.

These parameters may additionally include:

-   -   the geometry of sensor 101, or in other words sensor surface 110        as well as the shape and relative arrangement of pixels 104 on        this surface,    -   the noise generated by electronic unit 102,    -   the equation for conversion of light flux to pixel value.

b) Parameters associated with the intrinsic technical characteristics ofimage-capture appliance 1, determined during the phase of manufacture ofimage-capture appliance 1 and, in particular:

-   -   the exact positioning of the lenses in optical system 100 of the        configuration used,    -   the exact positioning of optical system 100 relative to sensor        101.

c) Parameters associated with the technical characteristics ofimage-capture appliance 1, determined at the moment of capture of image103 and, in particular:

-   -   the position and orientation of sensor surface 110 relative to        scene 3,    -   the adjustments used,    -   the external factors, such as temperature, if they have an        influence.

d) The user's preferences, especially the color temperature to be usedfor image restitution. For example, these preferences are selected bythe user by means of pushbuttons.

Observation Point, Observation Direction

Referring to FIG. 1, a description will now be given of what isunderstood by observation point 105 and observation direction 106.

Mathematical surface 10 is defined as a surface that is geometricallyassociated with sensor surface 110. For example, if the sensor surfaceis plane, it will be possible for mathematical surface 10 to coincidewith the sensor surface.

Observation direction 106 is defined as a line passing through at leastone point of scene 3 and through optical center 111. Observation point105 is defined as the intersection of observation direction 106 andsurface 10.

Observed Color, Observed Intensity

Referring to FIG. 1, a description will now be given of what isunderstood by observed color and observed intensity. Observed color isdefined as the color of the light emitted, transmitted or reflected bythe said scene 3 in the said observation direction 106 at a giveninstant, and observed from the said observation point 105. Observedintensity is defined as the intensity of the light emitted by the saidscene 3 in the said observation direction 106 at the same instant, andobserved from the said observation point 105.

The color can be characterized in particular by a light intensity thatis a function of wavelength, or else by two values as measured by acalorimeter. The intensity can be characterized by a value such asmeasured with a photometer.

The said observed color and the said observed intensity depend inparticular on the relative position of objects 107 in scene 3 and on theillumination sources present as well as on the transparency andreflection characteristics of objects 107 at the moment of observation.

Mathematical Projection, Mathematical Image, Mathematical Point,Mathematical Color of a Point, Mathematical Intensity of a Point,Mathematical Shape of a Point, Mathematical Position of a Point

Referring in particular to FIGS. 1, 5, 9 a, 9 b, 9 c and 9 d, adescription will be given of the concepts of mathematical projection 8,mathematical image 70, mathematical point, mathematical color of apoint, mathematical intensity of a point, mathematical shape 41 of apoint, and mathematical position 40 of a point.

Referring to FIG. 5, a description will now be given of how amathematical image 70 is constructed by specified mathematicalprojection 8 of at least one scene 3 on mathematical surface 10.

Firstly, a description will be given of what is understood by specifiedmathematical projection 8.

A specified mathematical projection 8 associates a mathematical image 70with:

-   -   a scene 3 at the moment of capture of an image 103,    -   and with the characteristics 74 used.

A specified mathematical projection 8 is a transformation with which thecharacteristics of each point of mathematical image 70 can be determinedfrom scene 3 at the moment of image capture and from the characteristics74 used.

Mathematical projection 8 is preferentially defined in the manner to bedescribed hereinafter.

Mathematical position 40 of the point is defined as the position ofobservation point 105 on mathematical surface 10.

Mathematical shape 41 of the point is defined as the geometric,punctiform shape of observation point 105.

Mathematical color of the point is defined as the observed color.

Mathematical intensity of the point is defined as the observedintensity.

Mathematical point is defined as the association of mathematicalposition 40, mathematical shape 41, mathematical color and mathematicalintensity for the observation point 105 under consideration.Mathematical image 70 is composed of the set of said mathematicalpoints.

The mathematical projection 8 of scene 3 is mathematical image 70.

Real Projection, Real Point, Real Color of a Point, Real Intensity of aPoint, Real Shape of a Point, Real Position of a Point

Referring in particular to FIGS. 3, 5, 9 a, 9 b, 9 c and 9 d, adescription will be given hereinafter of the concepts of real projection72, real point, real color of a point, real intensity of a point, realshape 51 of a point, and real position 50 of a point.

During image capture, image-capture appliance 1 associates an image 103of scene 3 with the characteristics 74 used. The light originating fromscene 3 in an observation direction 106 passes through optical system100 and arrives at sensor surface 110.

For the said observation direction, there is then obtained what isdefined as a real point, which exhibits differences compared with themathematical point.

Referring to FIGS. 9 a to 9 d, a description will now be given of thedifferences between the real point and the mathematical point.

The real shape 51 associated with the said observation direction 106 isnot a point on the sensor surface, but it has the form of a cloud inthree-dimensional space, where it has an intersection with one or morepixels 104. These differences are due in particular to coma, sphericalaberration, astigmatism, grouping into pixels 104, chromatic aberration,depth of field, diffraction, parasitic reflections and field curvatureof image-capture appliance 1. They give an impression of blurring, or oflack of sharpness of image 103.

In addition, real position 50 associated with the said observationdirection 106 exhibits a difference compared with mathematical position40 of a point. This difference is due in particular to the geometricdistortion, which gives an impression of deformation: for example,vertical walls appear to be curved. It is also due to the fact that thenumber of pixels 104 is limited, and that consequently the real position50 can have only a finite number of values.

In addition, the real intensity associated with the said observationdirection 106 exhibits differences compared with the mathematicalintensity of a point. These differences are due in particular to gammaand vignetting: for example, the edges of image 103 appear to be darker.Furthermore, noise may be added to the signal.

Finally, the real color associated with the said observation direction106 exhibits differences compared with the mathematical color of apoint. These differences are due in particular to gamma and the colorcast. Furthermore, noise may be added to the signal.

A real point is defined as the association of the real position 50, thereal shape 51, the real color and the real intensity for the observationdirection 106 under consideration.

The real projection 72 of scene 3 is composed of the set of real points.

Parameterizable Transformation Model, Parameters, Corrected Image

A parameterizable transformation model 12 (or parameterizabletransformation 12 for short) is defined as a mathematical transformationin which a corrected image 71 can be obtained from an image 103 and fromthe value of parameters. As indicated hereinbelow, the said parameterscan in particular be calculated from the characteristics 74 used.

By means of the said transformation, it is possible in particular todetermine, for each real point of image 103, the corrected position ofthe said real point, the corrected color of the said real point, thecorrected intensity of the said real point, and the corrected shape ofthe said real point, from the value of the parameters, from the realposition of the said real point and from the values of the pixels ofimage 103. As an example, the corrected position can be calculated bymeans of polynomials of fixed degree as a function of the real position,the coefficients of the polynomials depending on the value of theparameters. The corrected color and the corrected intensity can be, forexample, weighted sums of the values of the pixels, the coefficientsdepending on the value of the parameters and on the real position, orelse can be nonlinear functions of the values of the pixels of image103.

The parameters can include in particular: the focal length of opticalsystem 100 of the configuration used, or a related value such as theposition of a group of lenses, the focusing of optical system 100 of theconfiguration used, or a related value such as the position of a groupof lenses, the aperture of optical system 100 of the configuration used,or a related value such as the position of the diaphragm.

Difference Between the Mathematical Image and the Corrected Image

Referring to FIG. 5, the difference 73 between mathematical image 70 andcorrected image 71 for a given scene 3 and given characteristics 74 usedis defined as one or more values determined from numbers characterizingthe position, color, intensity, and shape of all or part of thecorrected points and of all or part of the mathematical points.

For example, the difference 73 between mathematical image 70 andcorrected image 71 for a given scene 3 and given characteristics 74 usedcan be determined as follows:

-   -   There are chosen characteristic points which, for example, may        be the points of an orthogonal array 80 of regularly disposed        points, as illustrated in FIG. 10.    -   The difference 73 is calculated, for example, by taking, for        each characteristic point, the sum of the absolute values of the        differences between each number characterizing position, color,        intensity and shape respectively for the corrected point and for        the mathematical point. The sum function of the absolute values        of the differences may be replaced by another function such as        the mean, the sum of the squares or any other function with        which the numbers can be combined.

Reference Scene

A reference scene 9 is defined as a scene 3 for which certaincharacteristics are known. As an example, FIG. 4 a shows a referencescene 9 composed of a paper sheet bearing regularly disposed, solidblack circles. FIG. 4 b shows another paper sheet bearing the samecircles, with the addition of colored lines and areas. The circles areused to measure the real position 50 of a point, the lines to measurethe real shape 51 of a point, and the colored areas to measure the realcolor of a point and the real intensity of a point. This reference scene9 may be composed of a material other than paper.

Reference Image

Referring to FIG. 12, a definition will now be given of the concept ofreference image 11. A reference image 11 is defined as an image ofreference scene 9 obtained with image-capture appliance 1.

Synthetic Image, Synthetic-Image Class

Referring to FIG. 12, a definition will now be given of the concept ofsynthetic image and of synthetic-image class 7. A synthetic image isdefined as a mathematical image 70 obtained by mathematical projection 8of a reference scene 9. A synthetic-image class 7 is defined as a set ofmathematical images 70 obtained by mathematical projection 8 of one ormore reference scenes 9 for one or more sets of characteristics 74 used.In the case in which there is only one reference scene 9 and only oneset of characteristics 74 used, the synthetic-image class 7 comprisesonly one synthetic image.

Transformed Image

Referring to FIG. 12, a definition will now be given of the concept oftransformed image 13. A transformed image 13 is defined as the correctedimage obtained by application of a parameterizable transformation model12 to a reference image 11.

Transformed Image Close to a Synthetic-image Class, Deviation

Referring to FIG. 12, a description will now be given of the concept oftransformed image 13 close to a synthetic-image class 7 and of theconcept of deviation 14.

The difference between a transformed image 13 and a synthetic-imageclass 7 is defined as the smallest difference between the saidtransformed image 13 and any one of the synthetic images of the saidsynthetic-image class.

A description will next be given of how to choose, among theparameterizable transformation models 12, that with which each referenceimage 11 can be transformed to a transformed image 13 close to thesynthetic-image class 7 of the reference scene 9 corresponding to thesaid reference image 11, in different cases of reference scenes 9 andcharacteristics 74 used.

-   -   In the case of a given reference scene 9 associated with a set        of given characteristics 74 used, there is chosen the        parameterizable transformation 12 (and its parameters) with        which the reference image 11 can be transformed to the        transformed image 13 that exhibits the smallest difference        compared with synthetic-image class 7. Synthetic-image class 7        and transformed image 13 are then said to be close. Deviation 14        is defined as the said difference.    -   In the case of a group of given reference scenes associated with        sets of given characteristics 74 used, the parameterizable        transformation 12 (and its parameters) is chosen as a function        of the differences between the transformed image 13 of each        reference scene 9 and the synthetic-image class 7 of each        reference scene 9 under consideration. There is chosen the        parameterizable transformation 12 (and its parameters) with        which the reference images 11 can be transformed to transformed        images 13 such that the sum of the said differences is        minimized. The sum function may be replaced by another function        such as the product. Synthetic-image class 7 and transformed        images 13 are then said to be close. Deviation 14 is defined as        a value obtained from the said differences, for example by        calculating the mean thereof.    -   In the case in which certain characteristics 74 used are        unknown, it is possible to determine them from the capture of a        plurality of reference images 11 of at least one reference scene        9. In this case, there are simultaneously determined the unknown        characteristics and the parameterizable transformation 12 (and        its parameters) with which the reference images 11 can be        transformed to transformed images 13, such that the sum of the        said differences is minimized, in particular by iterative        calculation or by solving equations concerning the sum of the        said differences and/or their product and/or any other        appropriate combination of the said differences. Synthetic-image        class 7 and transformed images 13 are then said to be close. The        unknown characteristics may be, for example, the relative        positions and orientations of sensor surface 110 and of each        reference scene 9 under consideration. Deviation 14 is defined        as a value obtained from the said differences, for example by        calculating the mean thereof.

Best Transformation

The best transformation is defined as the transformation with which,among the parameterizable transformation models 12, each reference image11 can be transformed to a transformed image 13 close to synthetic-imageclass 7 of the reference scene 9 corresponding to the said referenceimage 11,

Calibration

Calibration is defined as a method with which data related to theintrinsic characteristics of image-capture appliance 1 can be obtained,for one or more configurations used, each composed of an optical system100 associated with an image-capture appliance 1.

Case 1: in the case in which there is only one configuration, the saidmethod includes the following stages:

-   -   the stage of mounting the said optical system 100 on the said        image-capture appliance 1,    -   the stage of choosing one or more reference scenes 9,    -   the stage of choosing several characteristics 74 used,    -   the stage of capturing images of the said reference scenes 9 for        the said characteristics used,    -   the stage of calculating the best transformation for each group        of reference scenes 9 corresponding to the same characteristics        74 used.

Case 2: in the case in which all the configurations corresponding to agiven image-capture appliance 1 and to all optical systems 100 of thesame type are taken into consideration, the said method includes thefollowing stages:

-   -   the stage of choosing one or more reference scenes 9,    -   the stage of choosing several characteristics 74 used,    -   the stage of calculating images 103 from characteristics 74 used        and in particular from formulas for optical system 100 of the        configuration used and from values of parameters, by means, for        example, of software for calculating the optical system by ray        tracing,    -   the stage of calculating the best transformation for each group        of reference scenes 9 corresponding to the same characteristics        used.

Case 3: in the case in which all the configurations corresponding to agiven optical system 100 and to all the image-capture appliances 1 ofthe same type are taken into consideration, the said method includes thefollowing stages:

-   -   the stage of mounting the said optical system 100 on an        image-capture appliance 1 of the type under consideration,    -   the stage of choosing one or more reference scenes 9,    -   the stage of choosing several characteristics 74 used,    -   the stage of capturing images of the said reference scenes 9 for        the said characteristics used,    -   the stage of calculating the best transformation for each group        of reference scenes 9 corresponding to the same characteristics        used.

Calibration can be performed preferentially by the manufacturer ofimage-capture appliance 1, for each appliance and configuration in case1. This method is more precise but imposes more limitations and ishighly suitable in the case in which optical system 100 is notinterchangeable.

Alternatively, calibration can be performed by the manufacturer ofimage-capture appliance 1, for each appliance type and configuration incase 2. This method is less precise but is simpler.

Alternatively, calibration can be performed by the manufacturer ofimage-capture appliance 1, for each optical system 100 and type ofappliance in case 3. This method is a compromise in which one opticalsystem 100 can be used on all image-capture appliances 1 of one type,without repeating the calibration for each combination of image-captureappliance 1 and optical system 100.

Alternatively, calibration can be performed by the appliance seller orinstaller, for each image-capture appliance 1 and configuration in case1.

Alternatively, calibration can be performed by the appliance seller orinstaller, for each optical system 100 and type of appliance in case 3.

Alternatively, calibration can be performed by the appliance user, foreach appliance and configuration in case 1.

Alternatively, calibration can be performed by the appliance user, foreach optical system 100 and type of appliance in case 3.

Design of the Digital Optical System

Design of the digital optical system is defined as a method for reducingthe cost of optical system 100, by:

-   -   designing an optical system 100 having defects, especially in        positioning of real points, or choosing the same from a catalog,    -   reducing the number of lenses, and/or    -   simplifying the shape of the lenses, and/or    -   using less expensive materials, processing operations or        manufacturing processes.

The said method includes the following stages:

-   -   the stage of choosing an acceptable difference (within the        meaning defined hereinabove),    -   the stage of choosing one or more reference scenes 9,    -   the stage of choosing several characteristics 74 used.

The said method also includes iteration of the following stages:

-   -   the stage of choosing an optical formula that includes in        particular the shape, material and arrangement of the lenses,    -   the stage of calculating images 103 from the characteristics 74        used and in particular from the formulas for optical system 100        of the configuration used, by employing, for example, software        for calculating the optical system by ray tracing, or by making        measurements on a prototype,    -   the stage of calculating the best transformation for each group        of reference scenes 9 corresponding to the same characteristics        74 used,    -   the stage of verifying if the difference is acceptable, until        the difference is acceptable.

Formatted Information

Formatted information 15 associated with image 103, or formattedinformation 15, is defined as all or part of the following data:

-   -   data related to the intrinsic technical characteristics of        image-capture appliance 1, especially the distortion        characteristics, and/or    -   data related to the technical characteristics of image-capture        appliance 1 at the moment of image capture, especially the        exposure time, and/or    -   data related to the preferences of the said user, especially the        color temperature, and/or    -   data related to the deviations 14.

Database of Characteristics

A database 22 of characteristics or database 22 is defined as a databasecontaining formatted information 15 for one or more image-captureappliances 1 and for one or more images 103.

The said database 22 of characteristics can be stored in centralized ordistributed manner, and in particular can be:

-   -   integrated into image-capture appliance 1,    -   integrated into optical system 100,    -   integrated into a removable storage device,    -   integrated into a PC or other computer connected to the other        elements during image capture,    -   integrated into a PC or other computer connected to the other        elements after image capture,    -   integrated into a PC or other computer capable of reading a        storage medium shared with image-capture appliance 1,    -   integrated into a remote server connected to a PC or other        computer, itself connected to the other image-capture elements.

Fields

Referring to FIG. 8, a definition will now be given of the concept offields 90. The formatted information 15 associated with image 103 can berecorded in several forms and structured into one or more tables, but itcorresponds logically to all or part of fields 90, comprising:

(a) the focal distance,

(b) the depth of field

(c) the geometric defects.

The said geometric defects include geometric defects of image 103characterized by the parameters associated with the filmingcharacteristics 74 and a parameterizable transformation representing thecharacteristics of image-capture appliance 1 at the moment of filming.By means of the said parameters and of the said parameterizabletransformation, it is possible to calculate the corrected position of apoint of image 103.

The said geometric defects also include the vignetting characterized bythe parameters associated with filming characteristics 74 and aparameterizable transformation representing the characteristics ofimage-capture appliance 1 at the moment of filming. By means of the saidparameters and the said parameterizable transformation, it is possibleto calculate the corrected intensity of a point of image 103.

The said geometric defects also include the color cast characterized bythe parameters associated with filming characteristics 74 and aparameterizable transformation representing the characteristics ofimage-capture appliance 1 at the moment of filming. By means of the saidparameters and the said parameterizable transformation, it is possibleto calculate the corrected color of a point of image 103.

The said fields 90 also include (d) the sharpness of image 103.

The said sharpness includes the blurring in resolution of image 103characterized by the parameters associated with filming characteristics74 and a parameterizable transformation representing the characteristicsof image-capture appliance 1 at the moment of filming. By means of thesaid parameters and the said parameterizable transformation, it ispossible to calculate the corrected shape of a point of image 103.Blurring covers in particular coma, spherical aberration, astigmatism,grouping into pixels 104, chromatic aberration, depth of field,diffraction, parasitic reflections and field curvature.

The said sharpness also includes the blurring in depth of field, inparticular spherical aberrations, coma and astigmatism. The saidblurring depends on the distance of the points of scene 3 relative toimage-capture appliance 1, and it is characterized by the parametersassociated with filming characteristics 74 and a parameterizabletransformation representing the characteristics of image-captureappliance 1 at the moment of filming. By means of the said parametersand of the said parameterizable transformation, it is possible tocalculate the corrected shape of a point of image 103.

The said fields 90 also include (e) parameters of the quantizationmethod. The said parameters depend on the geometry and physics of sensor101, on the architecture of electronic unit 102 and on any processingsoftware that may be used.

The said parameters include a function that represents the variations ofintensity of a pixel 104 as a function of wavelength and light fluxderived from the said scene 3. The said function includes in particulargamma information.

The said parameters also include:

-   -   the geometry of the said sensor 101, especially the shape, the        relative position and the number of sensitive elements of the        said sensor 101,    -   a function representative of the spatial and temporal        distribution of noise of image-capture appliance 1,    -   a value representative of the exposure time for image capture.

The said fields 90 also include (f) parameters of the digital-processingoperations performed by image-capture appliance 1, especially digitalzoom and compression. These parameters depend on the processing softwareof image-capture appliance 1 and on the user's adjustments.

The said fields 90 also include:

(g) parameters representative of the user's preferences, especially asregards the degree of blurring and the resolution of image 103.

(h) the deviations 14.

Calculation of Formatted Information

The formatted information 15 can be calculated and recorded in database22 in several stages.

a) A stage at the end of design of image-capture appliance 1.

By means of this stage it is possible to obtain intrinsic technicalcharacteristics of image-capture appliance 1, and in particular:

-   -   the spatial and temporal distribution of the noise generated by        electronic unit 102,    -   the formula for conversion of light flux to pixel value,    -   the geometry of sensor 101.

b) A stage at the end of calibration or design of the digital opticalsystem.

By means of this stage it is possible to obtain other intrinsictechnical characteristics of image-capture appliance 1, and inparticular, for a certain number of values of characteristics used, thebest associated transformation and the associated deviation 14.

c) A stage in which the user's preferences are chosen by means ofpushbuttons, menus or removable media, or of connection to anotherdevice.

d) An image capture stage.

By means of this stage (d) it is possible to obtain technicalcharacteristics of image-capture appliance 1 at the moment of imagecapture, and in particular the exposure time, which is determined by themanual or automatic adjustments made.

By means of stage (d) it is also possible to obtain the focal distance.The focal distance is calculated from:

-   -   a measurement of the position of the group of lenses of variable        focal length of optical system 100 of the configuration used, or    -   a set value input to the positioning motor, or    -   a manufacturer's value if the focal length is fixed.

The said focal distance can then be determined by analysis of thecontent of image 103.

By means of stage (d) it is also possible to obtain the depth of field.The depth of field is calculated from:

-   -   a measurement of the position of the group of focusing lenses of        optical system 100 of the configuration used, or    -   a set value input to the positioning motor, or    -   a manufacturer's value if the depth of field is fixed.

By means of stage (d) it is also possible to obtain the defects ofgeometry and of sharpness. The defects of geometry and of sharpnesscorrespond to a transformation calculated by means of a combination oftransformations of the database 22 of characteristics obtained at theend of stage (b). This combination is chosen to represent the values ofparameters corresponding to the characteristics 74 used, especially thefocal distance.

By means of stage (d) it is also possible to obtain the parameters ofdigital processing performed by image-capture appliance 1. Theseparameters are determined by the manual or automatic adjustments made.

The calculation of formatted information 15 according to stages (a) to(d) can be performed by:

-   -   a device or software integrated into image-capture appliance 1,        and/or    -   driver software in a PC or other computer, and/or    -   software in a PC or other computer, and/or    -   a combination of the three.

The foregoing transformations in stage (b) and stage (d) can be storedin the form of:

-   -   a general mathematical formula,    -   a mathematical formula for each point,    -   a mathematical formula for certain characteristic points.

The mathematical formulas can be described by:

-   -   a list of coefficients,    -   a list of coefficients and coordinates.

By means of these different methods it is possible to reach a compromisebetween the size of the memory available for storage of the formulas andthe calculating power available for calculation of the corrected images71.

In addition, in order to retrieve the data, identifiers associated withthe data are recorded in database 22. These identifiers include inparticular:

-   -   an identifier of the type and of the reference of image-capture        appliance 1,    -   an identifier of the type and of the reference of optical system        100, if it is removable,    -   an identifier of the type and of the reference of any other        removable element having a link to the stored information, an        identifier of image 103,    -   an identifier of the formatted information 15.

Completed Image

As described by FIG. 11, a completed image 120 is defined as the image103 associated with the formatted information 15. This completed image120 can preferentially have the form of a file. Completed image 120 canalso be distributed into a plurality of files.

Completed image 120 can be calculated by image-capture appliance 1. Itcan also be calculated by an external calculating device, such as acomputer.

Image-Processing Software

Image-processing software 4 is defined as software that accepts one ormore completed images 120 as input and that performs processingoperations on these images. These processing operations can include inparticular:

-   -   calculating a corrected image 71,    -   performing measurements in the real world,    -   combining several images,    -   improving the fidelity of the images relative to the real world,    -   improving the subjective quality of images,    -   detecting objects or persons 107 in a scene 3,    -   adding objects or persons 107 to a scene 3,    -   replacing or modifying objects or persons 107 in a scene 3,    -   removing shadows from a scene 3,    -   adding shadows to a scene 3,    -   searching for objects in an image base.

The said image-processing software can be:

-   -   integrated into image-capture appliance 1,    -   run on calculating means 17 connected to image-capture appliance        1 by transmission means 18.

Digital Optical System

A digital optical system is defined as the combination of animage-capture appliance 1, a database 22 of characteristics and acalculating means 17 that permits:

-   -   image capture of an image 103,    -   calculation of the completed image,    -   calculation of the corrected image 71.

Preferentially, the user obtains corrected image 71 directly. If hewishes, the user may demand suppression of automatic correction.

The database 22 of characteristics may be:

-   -   integrated into image-capture appliance 1,    -   integrated into a PC or other computer connected to the other        elements during image capture,    -   integrated into a PC or other computer connected to the other        elements after image capture,    -   integrated into a PC or other computer capable of reading a        storage medium shared with image-capture appliance 1,    -   integrated into a remote server connected to a PC or other        computer, itself connected to the other image-capture elements.

Calculating means 17 may be:

-   -   integrated onto a component together with sensor 101,    -   integrated onto a component together with part of electronics        unit 102,    -   integrated into image-capture appliance 1,    -   integrated into a PC or other computer connected to the other        elements during image capture,    -   integrated into a PC or other computer connected to the other        elements after image capture,    -   integrated into a PC or other computer capable of reading a        storage medium shared with image-capture appliance 1,    -   integrated into a remote server connected to a PC or other        computer, itself connected to the other image-capture elements.

Processing of the Complete Chain

The foregoing paragraphs have essentially presented precise details ofthe concepts and description of the method and system according to theinvention for providing, to image-processing software 4, formattedinformation 15 related to the characteristics of image-capture appliance1.

In the paragraphs to follow, an expanded definition will be given of theconcepts and a supplemented description will be given of the method andsystem according to the invention for providing, to image-processingsoftware 4, formatted information 15 related to the characteristics ofimage-restitution means 19. In this way the processing of a completechain will be explained.

By means of the processing of the complete chain, it is possible:

-   -   to improve the quality of image 103 from one end of the chain to        the other, to obtain a restituted image 191 while correcting the        defects of image-capture appliance 1 and of image-restitution        means 19, and/or    -   to use optical systems of lower quality and of lower cost in a        video projector in combination with software for improvement of        image quality.

Definitions Associated with the Image-Restitution Means

On the basis of FIGS. 2 and 6, a description will now be given of howthe characteristics of an image-restitution means 19 such as a printer,a visual display screen or a projector are taken into account in theformatted information 15.

The supplements or modifications to be made to the definitions in thecase of an image-restitution means 19 may be inferred by analogy by aperson skilled in the art by analogy with the definitions provided inthe case of an image-capture appliance 1. Nevertheless, in order toillustrate this method, a description with reference in particular toFIG. 6 will now be given of the main supplements or modifications.

By restitution characteristics 95 used there are designated theintrinsic characteristics of image-restitution means 19, thecharacteristics of image-restitution means 19 at the moment of imagerestitution, and the user's preferences at the moment of imagerestitution. In the case of a projector in particular, the restitutioncharacteristics 95 used include the shape and position of the screenused.

By parameterizable restitution transformation model 97 (orparameterizable restitution transformation 97 for short), there isdesignated a mathematical transformation similar to parameterizabletransformation model 12.

By corrected restitution image 94 there is designated the image obtainedby application of parameterizable restitution transformation 97 to image103.

By mathematical restitution projection 96 there is designated amathematical projection that associates, with a corrected restitutionimage 94, a mathematical restitution image 92 on the mathematicalrestitution surface geometrically associated with the surface ofrestitution medium 190. The mathematical restitution points of themathematical restitution surface have a shape, position, color andintensity calculated from corrected restitution image 94.

By real restitution projection 90 there is designated a projection thatassociates a restituted image 191 with an image 103. The pixel values ofimage 103 are converted by the electronic unit of restitution means 19to a signal that drives the modulator of restitution means 19. Realrestitution points are obtained on restitution medium 190. The said realrestitution points are characterized by shape, color, intensity andposition. The phenomenon of grouping into pixels 104 describedhereinabove in the case of an image-capture appliance 1 does not occurin the case of an image-restitution means. On the other hand, an inversephenomenon occurs, with the result in particular that lines take on astaircase appearance.

Restitution difference 93 is designated as the difference betweenrestituted image 191 and mathematical restitution image 92. Thisrestitution difference 93 is obtained by analogy with difference 73.

By restitution reference there is designated an image 103 in which thevalues of pixels 104 are known.

By best restitution transformation there is designated for a restitutionreference and the restitution characteristics 95 used, that with whichimage 103 can be transformed to a corrected restitution image 94 suchthat its mathematical restitution projection 92 exhibits the minimumrestitution difference 93 compared with restituted image 191.

The methods of restitution calibration and of design of the digitaloptical restitution system are comparable with the methods ofcalibration and of design of the digital optical system in the case ofan image-capture appliance 1. Nevertheless, differences are present incertain stages, and in particular the following stages:

-   -   the stage of choosing a restitution reference;    -   the stage of performing restitution of the said restitution        reference;    -   the stage of calculating the best restitution transformation.

The formatted information 15 related to an image-capture appliance 1 andthat related to an image-restitution means 19 can be used end-to-end forthe same image.

In the foregoing, a description was given of the concept of field in thecase of an image-capture appliance 1. This concept is also applicable byanalogy in the case of image-restitution means 19. Nonetheless theparameters of the quantization method are replaced by the parameters ofthe signal-reconstitution method, meaning: the geometry of restitutionmedium 190 and its position, a function representing the spatial andtemporal distribution of the noise of image-restitution means 19.

Generalization of the Concepts

The technical features of which the invention is composed and which arespecified in the claims have been defined, described and illustrated byreferring essentially to image-capture appliances of digital type, or inother words appliances that produce digital images. It can be easilyunderstood that the same technical features are applicable in the caseof image-capture appliances that would be the combination of anappliance based on silver technology (a photographic or cinematographicappliance using sensitive silver halide films, negatives or reversalfilms) with a scanner for producing a digital image from the developedsensitive films. Certainly it is appropriate in this case to adapt atleast some of the definitions used. Such adaptations are within thecapability of the person skilled in the art. In order to demonstrate theobvious character of such adaptations, it is merely necessary to mentionthat the concepts of pixel and pixel value illustrated by referring toFIG. 3 must, in the case of the combination of an appliance based onsilver technology with a scanner, be applied to an elemental zone of thesurface of the film after this has been digitized by means of thescanner. Such transpositions of definitions are self-evident and can beextended to the concept of the configuration used. As an example, thelist of removable subassemblies of image-capture appliance 1 included inthe configuration used can be supplemented by the type of photographicfilm effectively used in the appliance based on silver technology.

Automatic Modification of the Quality of an Image

Referring to FIGS. 17, 13 a, 13 b and 13 c, a description will be givenof a practical example of the method and system according to theinvention for automatic modification of the quality of an image P2derived from or addressed to an appliance chain P3, which is alsodefined as the specified appliance chain.

In the practical example, the system according to the invention includesdata-processing means P76 to perform, for image P2, the following stagesof the method according to the invention:

-   -   the stage of compiling directories of the sources P50 of        formatted information 15 related to the appliances of set P75 of        appliances; these sources P50 may be in particular, depending on        the case, image file P58 containing image P2, the appliances, a        local and/or remote database 22, and means P53 for loading image        P2 or the modified image, an example being Twain-compliant        software used for a scanner; the sources compiled in this way        are defined as database 22,    -   the stage of searching automatically, among the said formatted        information 15 compiled in this way, for specific formatted        information P51 related to the said specified appliance chain        P3; a source can be used to update database 22, for example via        the Internet,    -   in the case in which the search for specific formatted        information P51 is unsuccessful for one of the appliances, the        stage of calculating the unknown formatted information, for        example by measuring the defects of the appliance, or by        simulating the appliance, or by calibrating the appliance        according to the method described hereinabove,    -   the stage of modifying the said image P2 automatically by means        of image-processing software P64 and/or image-processing        components P65, by taking into account the said specific        formatted information P51 obtained in this way.

By way of example, the method and system according to the invention willbe described for the application of restitution of an image of animage-capture appliance, whether it be a photographic appliance, a videofilming appliance, an echographic appliance, etc. Under theseconditions, it will be possible to use the characteristics of thefilming appliance (especially of optical type), of the sensor orphotosensitive surface (CCD, photosensitive film, etc.), of the scanner,of the processing software, of the information-transmission chainbetween the different appliances and of the printer for restitution ofan image of such an appliance. As will be seen hereinafter, it will bepossible to use other elements having their own particularcharacteristics in the image chain.

Each appliance is characterized by an identifier 60, by means of whichit is possible to identify the type of appliance and therefore to accessthe known characteristics related to this type of appliance andindirectly to obtain indices P52, the use of which will be describedhereinafter.

Certain appliances may be subject to special operating adjustments. Forexample, a capture appliance may be adjusted as a function of thefilming conditions, or a printer may be set to enlargement mode, etc.These particular modes of operation lead to variable characteristicsP55, which can be employed within the scope of the invention.Furthermore, these variable characteristics P55 may influence the fixedcharacteristics (or original characteristics) of the appliance or of theappliance chain P3.

FIG. 13 a illustrates a diagram of a practical example of the system ofthe invention.

In the upper part of this diagram there are illustrated appliances ordevices, which will be defined as peripheral appliances, which provideinformation, images and data to the system:

What is involved is:

-   -   an image 1 to be processed, which obviously contains image        information 61 but can also include data 62 concerning        characteristics of the filming medium and characteristics that        provide information on the image-capture conditions or on        subsequent manipulations of the image (examples being the focal        length used, or the redimensioning of the image). These        characteristics will be treated as variable characteristics 66        in the description hereinafter. The variable characteristics may        also be contained in the image itself or may be calculated from        the image.    -   an image-capture appliance APP1, which possesses inherent        characteristics and which may contain variable characteristics        66. The inherent characteristics are related to the type of        appliance or to each appliance, and they may be known through        knowledge of the appliance and of its original characteristics.        In particular, they may be known from its identifier 60, which        may be, for example, a bar code on the appliance or on a film,        and with which the system will associate these inherent        characteristics. Identifier 60 can be obtained in various ways        from the image, from the data 62, and/or by interrogating the        management software of the appliance, or the appliance itself,        or the user, which are symbolized by LOG/MAT/IMPR in FIG. 13 a.        Variable characteristics 66 are generally related to the        image-capture conditions, and may be those mentioned        hereinabove, which may be contained in the image, or in the        image-capture appliance or in both at the same time:    -   peripherals APP2 to APPn including in particular a peripheral        APP2 such as a printer or a scanner that has characteristics        related to the type of appliance and in particular reflecting        their defects, as well as variable characteristics 66 related to        the mode of use, examples being the enlargement factor for a        printer. A peripheral such as APPn may also be a        pseudo-peripheral and have the form of a file representing the        appliances or the functionalities and containing the        characteristics corresponding to these appliances or these        functionalities:    -   an image-capture appliance,    -   an image-restitution appliance,    -   an image-capture appliance which is different from appliance        APP1, for simulating photographs taken by that appliance, and        which can be referred to by the English term “lookalike”,    -   a simulation of an image-capture appliance which is different        from appliance APP1, for substituting for the appliance        mentioned hereinabove, and which, by analogy with the preceding        case, can be referred to by the term virtual “lookalike”,    -   characteristics with which the quality of an image can be        modified by taking into account vision defects of the eye of the        user, or with which special effects can be created,    -   characteristics with which software defects can be corrected or        modified, such as blurring induced by digital zoom,    -   software which performs processing on the image and introduces        defects, or which is provided with variable characteristics 66,        such as recoding or zoom,    -   installation characteristics, especially for a projector, which        are related to the error of square-on frontality or of flatness        of the screen, and which can be measured by a camera, for        example,    -   a combination of a plurality of appliances such as described        hereinabove.

These different devices APP1 to APPn as well as image 1 comprise anappliance chain P3. The processing of an image will take intoconsideration not only its inherent defects but also the defects of thedifferent appliances all of which will have an action on the image. Theset of these devices will be defined as appliance chain P3. The purposeof the system is to correct or modify the defects introduced by eachdevice of the chain into processing of the image.

Examples of the variable characteristics 66 that can be appropriatelytaken into account include:

-   -   the focal length of the optical system,    -   the redimensioning applied to the image (digital zoom factor:        enlargement of part of the image; and/or under-sampling:        reduction of the number of pixels of the image),    -   the nonlinear brightness correction, such as the gamma        correction,    -   the enhancement of contour, such as the level of deblurring        applied by appliance,    -   the noise of the sensor and of the electronic unit,    -   the aperture of the optical system,    -   the focusing distance,    -   the number of the frame on a film,    -   the underexposure or overexposure,    -   the sensitivity of the film or sensor,    -   the type of paper used in a printer,    -   the position of the center of the sensor in the image,    -   the rotation of the image relative to the sensor,    -   the position of a projector relative to the screen,    -   the white balance used,    -   the activation of a flash and/or its power,    -   the exposure time,    -   the sensor gain,    -   the compression,    -   the contrast,    -   another adjustment applied by the user of appliance, such as a        mode of operation,    -   another automatic adjustment of appliance,    -   another measurement performed by appliance.

The system possesses receiving interfaces C.VAR1, C.VAR2, . . . C.VARndesigned to receive the variable characteristics 66 explainedhereinabove. The characteristics derived from the image can betransmitted by the image itself or, as mentioned hereinabove, by thedata associated with the image. It is recalled that the variablecharacteristics 66 of the image can also be transmitted by theimage-capture appliance.

Interfaces ID1, ID2, . . . IDn are designed to receive the identifiers60 of the different peripherals APP1 to APPn.

Depending on the case, the concept of peripheral may correspond to oneor more appliances, which may or may not be of the same type. Thefollowing examples, each accompanied by a possible implementation ofidentifier 60 in the form of a coding and of a content, correspond toseveral of these cases:

-   -   to a given peripheral (for example, coding IA1: manufacturer's        name, type of peripheral, serial number of the peripheral),    -   to a given type of peripheral (for example, coding IA2:        manufacturer's name, type of peripheral),    -   to a given configuration (for example, coding IA3:        manufacturer's name, type of peripheral, type of interchangeable        objective mounted),    -   to a category of peripheral (for example, coding IA4, adapted to        disposable photo appliances: manufacturer's name, type of        appliance, frame number),    -   to a manufacturer (for example, coding IA5, for a manufacturer),    -   to a plurality of peripherals of a chain (for example, coding        IA6 in an equipment item for photographic printing, items of        formatted information related to a disposable appliance are        imported and combined with those of the scanner and printer, for        storage in a local database related to the chain, adapted        identifiers 60 are needed),    -   to an algorithm, such as a zoom algorithm (for example, coding        IA7: name of the algorithm, implementation, field indicating        whether image quality is to be modified before or after the        algorithm),    -   to a human being whose vision defects are to be corrected or        modified (for example, coding IA8: name of the person, country),    -   to a peripheral to be emulated and to which defects must be        added and not suppressed (for example, coding IA9:        manufacturer's name, type of appliance),    -   to a given peripheral version (for example, coding IA10:        manufacturer's name, type of peripheral, version of the software        of the peripheral),    -   to a protocol (for example, coding IA11: data derived from the        Twain protocol),    -   to a generic peripheral (for example, coding IA12: list of data        sources, field identifier; field value),

The system can then analyze the peripherals or appliances of appliancechain P3 and determine the identifiers 60 in various ways depending onthe case, in order to be able to interrogate the database.

A database contains, for each type of appliance, at least one item offormatted information representing the defects and the characteristicsof that appliance. The formatted information 15 may be related to thedefects P5 of the appliance in various ways. It may represent thedefects of the appliance. It may represent the inverse of the defects ofthe appliance. It may represent merely an approximation of the defects.It may represent the deviation between the defects of two appliances.From each identifier 60 provided by an interface such as interface ID1it is possible to obtain an item of formatted information such as 15.1,which is received temporarily in a circuit 20.1. Formatted informationrelated to appliances APP1, APP2, . . . APPn can be received in circuits20.1, 20.2, . . . 20.n.

The database may be integrated into the system or may be at least partlyremote.

In this case it can be managed by a third party, at least partly.

In the case, for example, of a digital photo appliance that corrects ormodifies its inherent defects, the database can be reduced to aregistration.

Operators 21.1, 21.2, . . . 21.n for processing formatted informationare designed to receive part of the values of the variablecharacteristics 66 provided by interfaces C.VAR1 to C.VARn as well asthe formatted information provided by circuits 20.1 to 20.N in such away that each operator processes a fraction of the formatted informationby means of one or more variable characteristics 66 and provides an itemof modified formatted information to an intermediate circuit 22.1 to22.n. For example, operator 21.1 receives the item of formattedinformation 15.1 depending on focal length, processes it by means of thevalue of variable characteristic 66 (the value of the focal length)provided by interface C.VAR1, and provides an item of modified formattedinformation 15.1′ that does not depend on focal length. As an example,FIG. 16.1 illustrates an appliance possessing characteristics that causedefects 704 to become apparent, leading in turn to formatted information15, as seen hereinabove. Variable characteristics 66 that represent avariable focal length 705, for example, also lead to formattedinformation (see FIG. 16.2).

Image-processing operators 23.1, 23.2, . . . 23.n are each designed toreceive an item of modified formatted information. The first operator23.1 receives an image to be processed, processes it by means of theitem of modified formatted information 15.1′, and provides a modifiedimage. This is received by the following operator 23.2, which processesit by means of the item of modified formatted information 15.2′ andprovides a new modified image, and so on until the last operator 23.n,which provides a final modified image.

Possibly, if an image-processing operator does not receive any modifiedformatted information, the image received by such an operator is notmodified and is transmitted as is to the following operator or to theoutput or, for example, default formatted information may be used.

Finally, the entire operation of the system, and in particular theexchange of information and data between the different elements of thesystem, can be managed by a central control unit 25.

Under these conditions, central control unit 25 will be in charge ofsearching automatically, within database 22, for formatted informationhaving addresses that are given by interfaces ID1, ID2, . . . IDn.Central unit 25 manages the search for this information and activatesoperators 21.1 to 21.n for processing the formatted information and thenimage-processing operators 23.1 to 23.n. If necessary, the operators maybe located on different remote but interconnected systems.

FIG. 13 b represents an alternative embodiment of the system accordingto the invention. In this alternative embodiment, the items of modifiedformatted information are combined into a single item of formattedinformation, and they modify the quality of the image to be processed.For this purpose, one operator 23.t replaces the operators 23.1 to 23.n.That operator receives and combines the different items of modifiedformatted information, and makes it possible to modify the quality ofthe image to be processed, in order to provide a modified image.

Furthermore, according to an alternative embodiment that is alsoapplicable to the system of FIG. 13 a, it is provided, as indicated inFIG. 13 c, that the variable characteristics 66 of an appliance and itsidentifier 60 be combined to enable direct access within database 22 toan item of modified formatted information. For example, the variablecharacteristics 66 provided by C.VAR1 are combined with an identifierID1 to form an item of modified formatted information 15.1, which istransmitted to 22.1. It is clear that in FIG. 13 c, this arrangement isprovided only for the item of modified formatted information 15.1′, butit could be applied to all or part of the other formatted information.The system provides a modified image at the output of operator 23.n forFIG. 13 a and 23. and for FIGS. 13 b and 13 c. FIG. 16.5 illustrates thecase in which, to a modified image 61 c, there is added associatedinformation 62 c, which can be:

-   -   a digital signature of the image,    -   correction data, or in other words modified formatted        information or its equivalent, or simply an indicator, thus        indicating that the image has been corrected or modified,    -   the data 62 or information P63 associated with original image 1,        modified or updated if necessary to reflect the processing        operations applied to the image, examples being data in Exif or        PIM format,    -   or both types of data.

The practical examples of FIGS. 13 a to 13 c can be applied to all ofthe defects or to each defect.

For example, it is possible to correct the distortion and blurring ofappliance APP1, then the distortion and blurring of APP2, etc.

According to another example, it is also possible to correct distortionof APP1, then distortion of APP2, etc., then blurring of APP1, thenblurring of APP2, etc.

By generalizing in the case of a plurality of defects and a plurality ofappliances, it is possible to combine the approaches of bothembodiments.

Referring to FIG. 14 a, a description will now be given of a simplifiedpractical example of the methods of the invention. This practicalexample is applied to an image-capture appliance. It is assumed that themethod is required to modify only the defects due to a single appliance,such as the image-capture appliance, and due to the adjustments of thatappliance.

As an example, the image is made available for processing in digitizedform by a digitizing device 400.1, by a digital capture appliance 400.2(digital photo appliance, or scanner, or other appliance), or by acompact disk 400.3.

In stage 401 of the method, a digitized image is available. In addition,the characteristics of the image-capture appliance and even the type ofthis appliance are known through any identification means, such as a barcode.

In stage 402 of the method, identifier 60 of the appliance is acquiredor calculated.

In stage 403, database 22 of the characteristics of the image-captureappliance can be accessed via identifier 60, for example by means ofindex P52. In fact, as mentioned hereinabove, a database is available inwhich appliance characteristics have in principle been registered forevery known appliance. Within the scope of the invention, thesecharacteristics represent the defects to be modified. Thus database 22is called in stage 403. In an alternative embodiment, the call to thedatabase may additionally take into account certain variablecharacteristics 66 obtained during stage 405, in order to obtaindirectly the formatted information that is pertinent for the valuesobtained in this way for variable characteristics 66.

In stage 404, an item of formatted information 15 that represents thecharacteristics (defects) of the corresponding appliance is read indatabase 22 at an address obtained from identifier 60.

Furthermore, along with the image to be processed, the system may beprovided if necessary with variable characteristics 66 (filmingconditions in particular) from a memory of the appliance, from softwarerelated to the appliance, or from information associated with the image.

These characteristics are therefore available in stage 405.

Thereafter (stage 406), the formatted information 15.1 to 15.n iscombined with the variable characteristics 66 to provide modifiedformatted information 15.1′ to 15.n′. This modified formattedinformation now contains all of the information with which the qualityof the image can be modified.

According to an alternative version of this stage 406, if the variablecharacteristics 66 and in particular their values for the image to beprocessed have been determined, they are used to determine, within theformatted information, a fraction of this formatted information thattakes into account these variable characteristics 66.

In stage 407, this modified formatted information is applied to theimage in order to process it and to correct or modify it. Thisprocessing is performed by means of operators assisted byimage-processing software.

In this way a modified image is obtained in stage 408.

It is quite evident that the foregoing method can function by using onlythe characteristics inherent to the appliance without using the variablecharacteristics 66. In this case the formatted data read in the databaseare used directly to process the image.

Referring to FIG. 14 b, a description will now be given of anotherpractical example of the invention. In this method and system, it isassumed that there is reason to take into account the diverse defects ofa plurality of appliances, and even those of all the appliances involvedin the processing of an image.

As in the example of FIG. 14 a, the method provides for acquisition bythe system of the digitized image, of the identifiers 60 of theappliances and of the variable characteristics 66.

During stage 501, the identifier 60 of an appliance is taken intoaccount, and makes it possible to address database 22 (stage 502) inorder to obtain one or more items of formatted information correspondingto this identifier 60.

A search is also made for the variable characteristics 66 related tothis appliance (stage 504).

During stage 505, the formatted information or certain items offormatted information are modified as a function of the characteristicvariables 66. As in the method described in connection with FIG. 14 b,once the variable characteristics 66 have been determined, they can beused to determine, among the formatted information, that which is usefuland which takes into account the variable characteristics 66. Theformatted information determined in this way is stored in memory.

Thereafter (stage 506), a test is performed to decide whether anotherappliance must be taken into account for modification of the quality ofthe image. In the diagram of FIG. 4 b, this test is represented in theform of the question “APP=APPn?”, meaning: “is the appliance being takeninto account the last of the appliances of the chain?”. If the answer isnegative, the process repeats stage 501 with the next appliance. If theanswer is positive, it means that all of the formatted informationrelated to the different appliances is in memory at the end of stage505.

The image is then processed in the course of stage 507 by formattedinformation related to the first appliance, and leads to a firstprocessed image. The system then takes into account the formattedinformation related to the next appliance and processes the previouslyprocessed image, and so on until all of the formatted information hasbeen processed, which in principle means until all the informationrelated to the different appliances of the chain has been taken intoaccount. The test “APP=APPn?” then responds positively. A modified imageis obtained and delivered.

It will be noted that the method of the invention can be implemented byperforming only a single test “APP=APPn?”. It would be possible toperform only the test of stage 508, which would achieve almost the sameresult.

In an alternative version of the method according to the invention, asillustrated in FIG. 14 c, it is provided that the different items offormatted information be combined in the course of stage 510, after allof the formatted information of all of the appliances has been obtained,or in other words on completion of stage 506. In this way, imageprocessing is performed one time during stage 507. As has been seenhereinabove, for an image to be processed, there may be needed aplurality of appliances, possibly including the image-capture appliance,a scanner, a printer, transmission systems, etc. Each appliance iscapable of inducing defects in the processing chain. There may also beneeded additional arrangements, which were defined hereinabove as“pseudo-peripherals” and which are intended to make modifications to theimage in accordance with a style or by application of defects thatcorrespond to these pseudo-peripherals.

In an alternative version of the method of the invention, it isconsidered that the set of appliances that, in an appliance chain P3,are necessary for processing an image, is composed of a singleappliance, which will be defined as virtual appliance 708 and whosedefects correspond to the equivalent of all or part of the defects ofthe different appliances of the chain. Thus appliances such as animage-capture appliance 706 (FIG. 16.4) and a printer 707 can berepresented by one virtual appliance 708, to which there correspondsvirtual formatted information 709. If it is considered that an item offormatted information can be a mathematical expression of physicalcharacteristics, an item of formatted information of a virtual appliance708 corresponding to two appliances can be the sum of two vectorscorresponding to the characteristics of these two appliances and/or tothe convolution of two mathematical functions. According to FIG. 16.4,there is therefore determined a virtual appliance 708 that exhibitsdefects equivalent to at least part of the original defects of thechain. The virtual formatted information 709 corresponding to thisvirtual appliance is determined. And the virtual formatted informationobtained is registered, or else this virtual formatted information issubstituted for the formatted information related to the originaldefects. The virtual formatted information can be accessed directly inthe database by means of an identifier 60 corresponding to the appliancechain P3 represented by the virtual appliance. Execution of the methodcan then be achieved more simply and more rapidly.

An example of organization of the method with which virtual formattedinformation can be obtained may be employed according to theorganizational diagram of FIG. 15. The characteristics of two appliancesare taken into account (stages 510 and 511). These characteristics arecombined in stage 512. The corresponding virtual formatted informationis calculated in stage 513. In stage 514, it is checked whether anotherappliance is needed in the virtual appliance chain. If yes, the processis repeated. If no, the process is terminated.

In the example of an integrated development laboratory, appliance chainP3 comprises a scanner, a photo appliance and a printer. The equivalentvirtual appliance exhibits the defects of the three appliances, and thetime for modification of the quality of the image may be dividedsubstantially by three.

In the case of an appliance with variable characteristics 66, it ispossible to determine the formatted information related to defects thatexhibit the said variable characteristic 66 in the following manner.

In the example in which the variable characteristics 66 are the focallength and the aperture, combinations are selected:

-   -   focal length=35 mm, aperture=f/2,    -   focal length=35 mm, aperture=f/8,    -   focal length=100 mm, aperture=f/8,    -   etc.

For each combination, the corresponding formatted information isdetermined by the method described hereinabove.

Formatted information that is a function of the focal length andaperture is deduced, for example by interpolation, in such a way thatthe database contains the formatted information necessary in stage 404.

It is therefore seen, as was seen hereinabove during the description ofFIG. 13 a, that an item of formatted information depending on a variablecharacteristic 66 such as the focal length is available. This item offormatted information is processed by means of the variablecharacteristic 66 to obtain an item of modified formatted information.

In the foregoing description, it was considered that the image to beprocessed was an image derived from an image-capture appliance, and wasto be displayed or printed. The invention is also applicable to anyimage-processing chain and thus also to a chain with which an image canbe projected. Thus an image-restitution chain will now be considered. Asin the foregoing practical examples of the method of the invention, thecharacteristics of the different appliances of the image-restitutionchain must be obtained. By means of these characteristics it is possibleto obtain formatted information for application of the method of theinvention.

A description will now be given of elements of detail or of alternativerevisions of the invention.

Firstly, during the description of FIG. 13 a, it was mentioned that theprovided characteristics making it possible to obtain formattedinformation could be characteristics designed to correct vision defects(such as astigmatism) of an observer 701, or to induce special effects.Under these conditions, the resulting formatted information 702 makes itpossible to modify the visual, graphic, calorimetric and other qualityof the image; as illustrated by FIG. 16.3, the formatted information 702related to vision defects of observer 701, for example, is processed asformatted information of appliance chain P3, and is even associated withsuch formatted information. In the foregoing, the processing of an imagewas considered; it is also possible to consider that the image islocated in a file P57, together with identifier 60 or an index P52 andpossibly the variable characteristics 66 of the capture appliance and ofany appliance that may have been involved in processing of the imageregistered in the file; it may also be considered that the image islocated in an image file P58, together with part of the formattedinformation. By extension, the invention is therefore equally applicableto the case in which the image as well as the formatted information isin database 22.

The value of the variable characteristics 66 can be determined by meansof information contained in file P57 or image file P58. Preferably, thisinformation will be registered in the file in a standard format such asthat of the EXIF standard known in the art. In this way, the system andthe method of the invention are applicable to the processing of imagesthat have been filmed and/or have already been processed by means ofappliances that were commercialized before the formatted informationcorresponding to such appliances was established.

It is quite evident that modification of the quality of the image can besimplified by taking into account only the defects of a limited numberof appliances of the chain, or even of a single appliance, and bycorrecting only those defects.

Furthermore, as was already envisioned in the description of FIG. 13 a,the method of the invention may be applied by simulating appliancesother than those constituting part of the appliance chain P3 being used.Likewise, formatted information related to an appliance or to a type ofappliances may be applicable to another appliance or to another type ofappliance, especially similar appliances. For example, as illustrated inFIG. 16.6, there is illustrated a plurality of lots 710.0, 710.1, 710.2of appliances. The formatted information concerns one type of appliance711, but this formatted information may also be applicable to a similarappliance 712, thus making it permissible, for example, to produce onlythe formatted information related to a single appliance of each type.

The invention is applicable to the modification, and in particular tothe improvement, of images processed or provided by an appliance or anappliance chain P3. An interesting application will be to modify onlythe defects or part of the defects of only certain appliances. Oneapplication may be to modify a defect only partly, in order, forexample, to establish a compromise between image quality and calculationtime.

Another object is application of the invention to machines forprocessing images in such a way as to induce defects, to impart aparticular style to the image or to simulate the presentation of anappliance, defined as reference appliance, or an appliance chain P3,defined as reference appliance chain, other than those used in the scopeof the application.

The invention is applicable to the design of integratedphoto-development laboratories. It can be employed on a computer.

Finally, it can be employed in projectors, in which case it permitsdifferent corrections to be made, including the parallax correction thatis common in the art of projection. For this purpose, a camera or aphoto appliance can be used to capture a test pattern projected onto thescreen.

Other examples of appliance chains can include:

-   -   computer camera (WEBCAM in English),    -   scanner,    -   digital photo appliance,    -   video camera,    -   printer,    -   screen,    -   projector,    -   games,    -   image-processing software,    -   teleconferencing system,    -   surveillance camera.

The following examples constitute appliance chains:

-   -   a single appliance,    -   an image-capture appliance and an image-restitution appliance,    -   a photo appliance, a scanner or a printer, for example in a        photo-printing Minilab,    -   a digital photo appliance or a printer, for example in a        photo-printing Minilab,    -   a scanner, a screen or a printer, for example in a computer,    -   a screen or projector, and the eye of a human being,    -   one appliance and another appliance which it is hoped can be        emulated,    -   a photo appliance and a scanner,    -   an image-capture appliance and image-processing software,    -   image-processing software and an image-restitution appliance,    -   a combination of the preceding examples,    -   another set of appliances.

The said method may be employed in different forms:

-   -   operating system,    -   extension of processing software, such as that known by the        trademark “PHOTOSHOP”,    -   embedded software,    -   integrated electronic components,    -   services on the Internet,    -   or any combination of these forms of employment, etc.

Color Image

Referring in particular to FIG. 18, a description will now be given ofthe concept of color image P21, of color plane P20, of specified colorP22, and of data P23 related to a specified color. The alternativeembodiment described hereinafter is applicable to the case in whichimage P2 is a color image P21. Color image P21 can be decomposed intocolor planes P20 in various ways: number of planes (1, 3 or more),precision (8 bits unsigned, 16 bits signed, floating, etc.) andsignificance of the planes (relative to a standard color space). Colorimage P21 can be decomposed in various ways into color planes P20: red,green, blue (RGB) or brightness, saturation, hue, etc.; on the otherhand, color spaces such as PIM exist, or negative pixel values arepossible in order to permit representation of subtractive colors, whichcannot be represented in positive RGB; finally, it is possible to encodea pixel value on 8 bits or 16 bits, or by using floating values. Theformatted information 15 includes data with which image P2 can bedecomposed into color planes P20 compatible with the different defectsP5 to be processed; each color plane being characterized by a specifiedcolor P22; the said formatted information 15 containing data P23 relatedto the said specified color, examples being coordinates in standard CIEor XYZ or LAB or sRGB color space; the said data P23 related to the saidspecified color making it possible to calculate the color plane P20 ofimage 1 and to determine the fraction of the said formatted information15 that can be employed appropriately to modify the quality of the saidcolor plane P20.

In the case of an appliance that is compatible with the PIM standard, itis possible, for example, to choose to work in positive color on 8 bitsin X, Y, Z space or to work on 16 bits signed in RGB space.

Measured Formatted Information, Extended Formatted Information

The formatted information 15 or a fraction of the formatted information15 can include measured formatted information P101 to illustrate a rawmeasurement, such as a mathematical field related to geometricdistortion defects at a certain number of characteristic points of anarray 80. The formatted information 15 or a fraction of the formattedinformation 15 can include extended formatted information P102, whichcan be calculated from measured formatted information P101, for exampleby interpolation for real points other than the characteristic points ofarray 80. In the foregoing, it has been seen that a formattedinformation item 15 might depend on variable characteristics 66.According to the invention, a combination P120 is defined as acombination composed of variable characteristics 66 and of values ofvariable characteristics, an example being a combination P120 composedof the focal length, of the focusing, of the diaphragm aperture, of thecapture speed, of the aperture, etc. and of associated values. It isdifficult to imagine how the formatted information 15 related todifferent combinations P120 can be calculated, all the more so becausecertain characteristics of combination P120, such as the focal lengthand the distance, can vary continuously.

The invention provides for calculating the formatted information 15 inthe form of extended formatted information P102 by interpolation frommeasured formatted information P101 related to a predetermined selectionof combinations P120 of known variable characteristics 66.

For example, measured formatted information P101 related to thecombination P120 of “focal length=2, distance=7, capture speed= 1/100”,to the combination of “focal length=10, distance=7, capture speed=1/100” and to the combination of “focal length=50, distance=7, capturespeed= 1/100” is used to calculate extended formatted information P102that depends on focal length as the variable characteristic 66. By meansof this extended formatted information P102, it is possible inparticular to determine formatted information related to the combinationof “focal length=25, distance=7 and capture speed= 1/100”.

The measured formatted information P101 and the extended formattedinformation P102 may exhibit an interpolation deviation P121. Theinvention may include the stage of selecting zero or one or morevariable characteristics 66, such that interpolation deviation P121 forthe extended formatted information P102 obtained for the variablecharacteristics 66 selected in this way is smaller than a predeterminedinterpolation threshold. In fact, certain variable characteristics 66may have a smaller influence than others on the defect P5, and the errorintroduced by making the approximation that these are constant maymerely be minimum; for example, the focusing adjustment may have merelya slight influence on the vignetting defect, and for this reason may notbe part of the variable characteristics 66 selected. The variablecharacteristics 66 may be selected at the moment of production of theformatted information 15. It results from the combination of technicalfeatures that the modification of image quality employs simplecalculations. It also results from the combination of technical featuresthat the extended formatted information P102 is compact. It also resultsfrom the combination of technical features that the eliminated variablecharacteristics 66 have the least influence on the defect P5. It resultsfrom the combination of technical features that image quality can bemodified with specified precision by means of the formatted information15.

Application of the Invention to Cost Reduction

Cost reduction is defined as a method and system for lowering the costof an appliance or of an appliance chain P3, especially the cost of. theoptical system of an appliance or of an appliance chain, the methodconsisting in:

-   -   reducing the number of lenses, and/or    -   simplifying the shape of the lenses, and/or    -   designing an optical system having defects P5 that are larger        than those desired for the appliance or the appliance chain, or        choosing the same from a catalog, and/or    -   using materials, components, processing operations or        manufacturing methods that are less costly for the appliance or        the appliance chain and that add defects P5.

The method and system according to the invention can be used to lowerthe cost of an appliance or of an appliance chain: it is possible todesign a digital optical system, to produce formatted information 15related to the defects P5 of the appliance or of the appliance chain, touse this formatted information to enable image-processing means, whetherthey are integrated or not, to modify the quality of images derived fromor addressed to the appliance or to the appliance chain, in such a waythat the combination of the appliance or the appliance chain with theimage-processing means is capable of capturing, modifying or restitutingimages of the desired quality at reduced cost.

1. A method of an image processing apparatus for modifying quality of atleast one image derived from or addressed to a specified appliancechain, the appliance chain including at least one image-captureappliance selected from a group including a photographic appliance, avideo camera, a camera connected to or integrated in a PC, a cameraconnected to or integrated in a personal digital assistant, a cameraconnected to or integrated in a telephone, a videoconferencing applianceor of a measuring camera, the appliances belonging to a set ofappliances and exhibiting defects that can be characterized by formattedinformation, the method comprising: producing formatted informationrelated to an appliance of at least one type by calibrating, among theset of appliances, said appliance, so as to obtain data related tointrinsic characteristics of said appliance; compiling directories ofsources of formatted information related to the appliances of the set ofappliances or to appliances of the same type; searching automatically,by the image processing apparatus, among the compiled formattedinformation, for specific formatted information related to the specifiedappliance chain, taking into account formatted information related tosaid appliance of said at least one type when the specified appliancechain comprises another appliance of said at least one type differentfrom said appliance; modifying, by the image processing apparatus, theimage automatically by image-processing software and/or image-processingcomponents, taking into account the searched specific formattedinformation, based on a determination that the formatted information forall the appliances of the appliance chain have been obtained, theappliance chain including a number of appliances that is not predefinedin the image processing apparatus; and providing one of the appliancesof said appliance chain with at least one variable characteristicdepending on the image, a fraction of the specific formatted informationbeing related to the defects of the appliance, the variablecharacteristic comprising one of: a focal length of an optical system, aredimensioning applied to an image, a nonlinear brightness correction, agamma correction, an enhancement of an image contour, a level ofdeblurring applied by the one appliance, an image noise characteristicof a sensor or an electronic device, an aperture of an optical system, afocusing distance, a number of frames in a film, an underexposure oroverexposure, a sensitivity of a film or sensor, a type of paper used ina printer, a position of a center of a sensor, a rotation of an imagerelative to a sensor, a position of a projector relative to a screen, awhite balance, an activation of a flash, a flash power, an exposuretime, a sensor gain, a compression factor, an image contrast, andanother image related adjustment, and an adjusted mode of operation, thedefects of the appliance are related to a characteristic of one of theoptical system, the sensor, the electronic device, or software in theappliance, the defects of the appliance include at least one of adistortion, a blurring, a vignetting, a chromatic aberration, arendering of colors, a flash uniformity, a sensor noise, a grain, anastigmatism, or a spherical aberration, and the searched specificformatted information include formatted information related to the atleast one variable characteristic depending on the image and that are afunction of adjustments of an image-capture appliance made in a step ofimage capture.
 2. A method according to claim 1, wherein the automaticsearching is performed by an index obtained directly or indirectly froman analysis of at least one of: the image, the appliances of theappliance chain, means for loading the image into the image-processingsoftware or components, means for loading the image modified by theimage-processing software or components to the at least oneimage-restitution appliance.
 3. A method according to claim 2, whereinthe appliances of the appliance chain are identified by identifiers, thesearching for the specific formatted information including determiningthe identifiers.
 4. A method according to claim 3, wherein the image,the index, and/or the identifier are contained in a same file; whereinit is possible to employ the method a posteriori in a case in whichcertain appliances of the chain were commercialized before the formattedinformation related to the certain appliances was established.
 5. Amethod according to claim 1, wherein the image and at least one part ofthe specific formatted information are contained in a same image file;wherein it is possible to search automatically for the formattedinformation in the same image file.
 6. A method according to claim 1,further comprising: storing at least part of the formatted informationin advance in a database; and updating the database.
 7. A methodaccording to claim 1, the method further comprising: determining a valueof the at least one variable characteristic for the image; determining afraction of the specific formatted information by taking into accountvalues obtained for the at least one variable characteristic; whereinemployment of the method for an appliance provided with a variablecharacteristic amounts to employment of the method for an appliance thatdoes not have any variable characteristic.
 8. A method according toclaim 7, wherein the image is contained in a file, and wherein todetermine the value of the at least one variable characteristic, datapresent in the file is used, in a desired format; wherein it is possibleto employ the method a posteriori in a case in which the applianceprovided with the at least one variable characteristic wascommercialized before the formatted information related to it wasestablished.
 9. A method according to claim 1, to modify quality of atleast one image derived from or addressed to an appliance chain, themethod further comprising: determining a virtual appliance exhibitingdefects equivalent to at least part of the defects, of at least oneappliance of the appliance chain; determining virtual formattedinformation related to the defects of the virtual appliance; determiningspecific formatted information related to the set of appliances of theappliance chain, the virtual formatted information is substituted forthe specified formatted information related to the original defects;whereby formatted information is obtained that is simpler to employ andwith which modifications to be made to the image can be calculated atleast one of more rapidly, using less memory, and with greaterprecision.
 10. A method according to claim 1, wherein the method isconfigured to modify the quality of at least one color plane of a colorimage, the color plane being characterized by a specified color, thespecific formatted information additionally including data related tothe specified color, wherein to modify the image, the color plane iscalculated using the data related to the specified color and to theimage.
 11. A method according to claim 1, the method further comprising,in a case in which the process of searching for the specific formattedinformation is unsuccessful for one of the appliances of the appliancechain, calculating unknown formatted information for the one of theappliances of the appliance chain.
 12. A method according to claim 11,the step of calculating unknown formatted information comprisingcalculating the unknown formatted information: by measuring the defectsof the appliance, and/or by simulating the appliance.
 13. A methodaccording to claim 11, the step of calculating unknown formattedinformation comprising calculating the unknown formatted information: byconstructing a synthetic-image class by specified mathematicalprojections of at least one reference scene onto a surface, by capturingat least one reference image of each reference scene by theimage-capture appliance, by choosing, within a set of parameterizabletransformation models, that with which the reference image can betransformed to a transformed image close to the synthetic-image class ofthe reference scene, the transformed image exhibiting a deviationcompared with the synthetic-image class; the unknown formattedinformation being composed at least partly of parameters of the chosenparameterizable transformation models.
 14. A method according to claim13, further comprising: calculating deviations between the transformedimage and the synthetic-image class; associating the deviations with theunknown formatted information; wherein it is possible to deducestandardized information about the scenes in three dimensions; whereinit is possible to combine a plurality of images obtained from aplurality of image-capture appliances having undergone the sameformatting process.
 15. A method according to claim 13, wherein one ofthe appliances of the appliance chain is provided with at least onevariable characteristic depending on the image, a fraction of thespecific formatted information being related to the defects of theappliance provided with the at least one variable characteristic, eachvariable characteristic being capable of being associated with a valueto form a combination composed of a set of the at least one variablecharacteristic and of the values; the method further comprisingdetermining the fraction of the unknown formatted information: byselecting predetermined combinations, by employing a process ofiteration of the method operation for each of the predeterminedcombinations, by employing a process of interpolation of the unknownformatted information related to an arbitrary combination, from theunknown formatted information obtained at an end of the iterationprocess.
 16. A method according to claim 11, further comprising, for animage-restitution appliance of the appliance chain, producing datacharacterizing the defects of the image-restitution appliance, theunknown formatted information being composed at least partly of the datacharacterizing the defects of the image-restitution appliance.
 17. Amethod according to claim 1, wherein the specific formatted informationrelated to one appliance or to a plurality of appliances of theappliance chain is determined such that it can be applied to similarappliances; wherein only a limited quantity of formatted information isneeded for the method to be employed.
 18. A method according to claim 1,wherein the image includes associated information, the operations of themethod being employed such that they conserve or modify the associatedinformation.
 19. A method according to claim 1, further comprisingassociating information with the modified image, including informationindicating the image has been modified.
 20. A method according to claim1, configured to modify visual quality of the image for an observer, theformatted information related to the defects of the appliances of theappliance chain additionally including the formatted information relatedto vision characteristics of the observer.
 21. An application of themethod according to claim 1, wherein an object of the application is toimprove the quality of the images processed by the image-processingsoftware or the image-processing components, by correcting for effectsof at least one of the defects of the appliances of the appliance chain;wherein the quality of the processed images is improved if not perfect,without having to rely on expensive appliances.
 22. An application ofthe method according to claim 1, wherein the quality of the imagesprocessed by the image-processing software or the image-processingcomponents is comparable with that of images produced with a referenceappliance chain.
 23. An application according to claim 21, theapplication being such that, for the quality of the processed images tobe comparable with that of images produced with a reference appliancechain, formatted information related to the appliance chain is producedby taking into account the defects of the reference appliance chain. 24.A system for modifying quality of at least one image derived from oraddressed to a specified appliance chain, the appliance chain includingat least one image-capture appliance selected from a group including aphotographic appliance, a video camera, a camera connected to orintegrated in a PC, a camera connected to or integrated in a personaldigital assistant, a camera connected to or integrated in a telephone, avideoconferencing appliance or of a measuring camera, the appliancesbelonging to a set of appliances and exhibiting defects characterized byformatted information; the system including, for the image,data-processing means for: producing formatted information related to anappliance of at least one type by calibrating, among the set ofappliances, said appliance, so as to obtain data related to intrinsiccharacteristics of said appliance; compiling directories of sources offormatted information related to the appliances of the set of appliancesor to appliances of the same type; searching automatically, among thecompiled formatted information, for specific formatted informationrelated to the specified appliance chain taking into account formattedinformation related to said appliance of said at least one type when thespecified appliance chain comprises another appliance of said at leastone type different from said appliance; modifying the imageautomatically by image-processing software and/or image-processingcomponents, taking into account the searched specific formattedinformation, based on a determination that the formatted information forall the appliances of the appliance chain have been obtained, theappliance chain including a number of appliances that is not predefinedin the data-processing means; and providing one of the appliances ofsaid appliance chain with at least one variable characteristic dependingon the image, a fraction of the specific formatted information beingrelated to the defects of the appliance, the variable characteristiccomprising one of: a focal length of an optical system, a redimensioningapplied to an image, a nonlinear brightness correction, a gammacorrection, an enhancement of an image contour, a level of deblurringapplied by the one appliance, an image noise characteristic of a sensoror an electronic device, an aperture of an optical system, a focusingdistance, a number of frames in a film, an underexposure oroverexposure, a sensitivity of a film or sensor, a type of paper used ina printer, a position of a center of a sensor, a rotation of an imagerelative to a sensor, a position of a projector relative to a screen, awhite balance, an activation of a flash, a flash power, an exposuretime, a sensor gain, a compression factor, an image contrast, andanother image related adjustment, and an adjusted mode of operation, thedefects of the appliance are related to a characteristic of one of theoptical system, the sensor, the electronic device, or software in theappliance, the defects of the appliance include at least one of adistortion, a blurring, a vignetting, a chromatic aberration, arendering of colors, a flash uniformity, a sensor noise, a grain, anastigmatism, or a spherical aberration, and the searched specificformatted information include formatted information related to the atleast one variable characteristic depending on the image and that are afunction of adjustments of an image-capture appliance made in a step ofimage capture.
 25. A system according to claim 24, wherein thedata-processing means performs the search automatically by an index, theindex being obtained directly or indirectly by an analysis of at leastone of: the image, the appliances of the appliance chain, means forloading the image into the image-processing software or components,means for loading the image modified by the image-processing software orcomponents to the at least one image-restitution appliance.
 26. A systemaccording to claim 25, wherein the appliances of the appliance chain areidentified by identifiers, the analysis including identification meansfor determining the identifiers.
 27. A system according to claim 26,wherein the image, the index, and/or the identifier are contained in afile.
 28. A system according to claim 24, wherein the image and at leastone part of the specific formatted information are contained in a sameimage file.
 29. A system according to claim 24, further comprising:storage means for storing at least part of the formatted information inadvance in a database; and updating means for updating the database. 30.A system according to claim 24, wherein one of the appliances of theappliance chain is provided with at least one variable characteristicdepending on the image, a fraction of the specific formatted informationbeing related to the defects of the appliance provided with the at leastone variable characteristic, the system further comprising calculatingmeans for determining: a value of the at least one variablecharacteristic for the image; a fraction of the specific formattedinformation by taking into account values obtained for the at least onevariable characteristic.
 31. A system according to claim 30, wherein theimage is contained in a file, the system being such that, to determinethe value of the at least one variable characteristic, the systemincludes data-processing means for processing data present in the file,in a desired format.
 32. A system according to claim 24, wherein, tomodify the quality of at least one image derived from or addressed to anappliance chain, the system includes data-processing means fordetermining: a virtual appliance exhibiting defects equivalent to atleast part of the defects, of at least one appliance of the appliancechain, the virtual formatted information related to the defects of thevirtual appliance, the system being such that, to determine the specificformatted information related to the set of appliances of the appliancechain, the data-processing means includes substitution means forsubstituting the virtual formatted information for the specificformatted information related to original defects.
 33. A systemaccording to claim 24, wherein to modify the quality of at least onecolor plane of a color image, the color plane is characterized by aspecified color, the specific formatted information additionallyincluding data related to the specified color, the system furthercomprising calculating means for calculating the color plane using thedata related to the specified color and to the image.
 34. A systemaccording to claim 24, further comprising, in a case in which theprocess of searching for the specific formatted information isunsuccessful for one of the appliances of the appliance chain,calculating means for calculating unknown formatted information for theone of the appliances of the appliance chain.
 35. A system according toclaim 34, wherein the calculating means for calculating the unknownformatted information includes means for processing means for measuringthe defects of the appliance and/or for simulating the appliance.
 36. Asystem according to claim 34, wherein the calculating means forcalculating the unknown formatted information includes means forconstructing a synthetic-image class by specified mathematicalprojections of at least one reference scene onto a surface, theimage-capture appliance capturing at least one reference image of eachreference scene, the calculating means calculating the unknown formattedinformation by choosing, within a set of parameterizable transformationmodels, that with which the reference image can be transformed to atransformed image close to the synthetic-image class of the referencescene, the transformed image exhibiting a deviation compared with thesynthetic-image class, the unknown formatted information being composedat least partly of parameters of the chosen parameterizabletransformation models.
 37. A system according to claim 36, the systemfurther comprising data-processing means for: calculating deviationsbetween the transformed image and the synthetic-image class; associatingthe deviations with the unknown formatted information.
 38. A systemaccording to claim 36, further comprising: information-processing meansfor determining the fraction of the unknown formatted information: byselecting predetermined combinations, by employing, for each of thepredetermined combinations, a process of iteration of the calculatingmeans and of the data-processing means, by employing a process ofinterpolation of the unknown formatted information related to anarbitrary combination, from the unknown formatted information obtainedat an end of the iteration process.
 39. A system according to claim 34,the system further comprising, for an image-restitution appliance of theappliance chain, data-processing means for producing data characterizingthe defects of the image-restitution appliance, the unknown formattedinformation being composed at least partly of the data characterizingthe defects of the image-restitution appliance.
 40. A system accordingto claim 24, wherein the specific formatted information related to oneappliance or to a plurality of appliances of the appliance chain isdetermined such that it can be applied to similar appliances.
 41. Asystem according to claim 24, wherein the image includes associatedinformation, the system being employed such that it conserves ormodifies the associated information.
 42. A system according to claim 24,the system further comprising data-processing means for associatinginformation with the modified image, including information indicatingthat it has been modified.
 43. A system according to claim 24,configured to modify a visual quality of the image for an observer, theformatted information related to the defects of the appliances of theappliance chain additionally including the formatted information relatedto the vision characteristics of the observer.
 44. The method accordingto claim 1, comprising: producing formatted information related to oneappliance of each type by calibrating, among the set of appliances, saidappliance, so as to obtain data related to the intrinsic characteristicsof one appliance of each type; searching automatically, among thecompiled formatted information, for specific formatted informationrelated to the specified appliance chain taking into account formattedinformation related to said one appliance of each type when thespecified appliance chain comprises another appliance of said typedifferent from said appliance.
 45. A system for modifying quality of atleast one image derived from or addressed to a specified appliancechain, the appliance chain including at least one image-captureappliance selected from a group including a photographic appliance, avideo camera, a camera connected to or integrated in a PC, a cameraconnected to or integrated in a personal digital assistant, a cameraconnected to or integrated in a telephone, a videoconferencing applianceor of a measuring camera, the appliances belonging to a set ofappliances and exhibiting defects characterized by formattedinformation; the system including, for the image, data-processing unitconfigured to produce formatted information related to an appliance ofat least one type by calibrating, among the set of appliances, saidappliance, so as to obtain data related to intrinsic characteristics ofsaid appliance; compile directories of sources of formatted informationrelated to the appliances of the set of appliances or to appliances ofthe same type; search automatically, among the compiled formattedinformation, for specific formatted information related to the specifiedappliance chain taking into account formatted information related tosaid appliance of said at least one type when the specified appliancechain comprises another appliance of said at least one type differentfrom said appliance; modify the image automatically by image-processingsoftware and/or image-processing components, taking into account thesearched specific formatted information, based on a determination thatthe formatted information for all the appliances of the appliance chainhave been obtained, the appliance chain including a number of appliancesthat is not predefined in the data-processing unit; and provide one ofthe appliances of said appliance chain with at least one variablecharacteristic depending on the image, a fraction of the specificformatted information being related to the defects of the appliance, thevariable characteristic comprising one of: a focal length of an opticalsystem, a redimensioning applied to an image, a nonlinear brightnesscorrection, a gamma correction, an enhancement of an image contour, alevel of deblurring applied by the one appliance, an image noisecharacteristic of a sensor or an electronic device, an aperture of anoptical system, a focusing distance, a number of frames in a film, anunderexposure or overexposure, a sensitivity of a film or sensor, a typeof paper used in a printer, a position of a center of a sensor, arotation of an image relative to a sensor, a position of a projectorrelative to a screen, a white balance, an activation of a flash, a flashpower, an exposure time, a sensor gain, a compression factor, an imagecontrast, and another image related adjustment, and an adjusted mode ofoperation, the defects of the appliance are related to a characteristicof one of the optical system, the sensor, the electronic device, orsoftware in the appliance, the defects of the appliance include at leastone of a distortion, a blurring, a vignetting, a chromatic aberration, arendering of colors, a flash uniformity, a sensor noise, a grain, anastigmatism, or a spherical aberration, and the searched specificformatted information include formatted information related to the atleast one variable characteristic depending on the image and that are afunction of adjustments of an image-capture appliance made in a step ofimage capture.
 46. A method according to claim 1, wherein the modifyingthe image automatically comprises successively processing the imagebased on the searched specific formatted information of each applianceof the appliance chain independent of the other searched specificformatted information of the appliance chain.
 47. A system according toclaim 24, wherein the data-processing means for modifying the imageautomatically includes means for successively processing the image basedon the searched specific formatted information of each appliance of theappliance chain independent of the other searched specific formattedinformation of the appliance chain.
 48. A system according to claim 45,wherein the data-processing unit is further configured to successivelyprocess the image based on the searched specific formatted informationof each appliance of the appliance chain independent of the othersearched specific formatted information of the appliance chain.